Bug #23300

AI can even hear slow movement

Added by kju almost 4 years ago. Updated about 2 years ago.

Status:Assigned Start date:08/10/2011
Priority:Normal Due date:11/01/2011
Assignee:Dwarden % Done:

0%

Category:AI Issues
Target version:-
Affected ArmA II version:1.60 BETA First affected build:
Reproduced by another DH user:No First affected ArmA II version:
I am using some Mods:No Single / Multi Player?:
I am using:OA only BIForumURL:
Reproducible for you:Yes NGUrl:
Related to content of DLC: WIKIurl:

Description

Preface
This may need some discussion first about sensible AI behavior.

Settings
Tested with:
  • 100% unit skill
  • veteran difficulty with 90% enemy skill
  • 1.59.83553 (latest beta - very important)

Obs
Back in OFP night SecOps missions often involved crawling very close to enemies,
like the mission to infiltrate the house of Guba on Kolgujev in the NW.

Since ArmA people complain about AI hearing too good.

In the given demo mission the player starts 50 meter behind an enemy infantry.
One can change the time, +3 hours, with radio ALPHA trigger.
It constantly shows the distance in the bottom to the enemy.

Now once the enemy picks you up by hearing you to getting close by behind,
you will see the knowsAbout value, subjectiveCost, positionAccuracy in chat.
These values are also logged to rpt along with the current distance.

Here is the summary of the results:

### walk
"Distance: 16.3243, knowsAbout: 0.324038, subjectiveCost: 0.134179, positionAccuracy: 18.6957" 
"Distance: 9.47541, knowsAbout: 0.9375, subjectiveCost: 1.65896e+006, positionAccuracy: 10.8794" 
"Distance: 4.12707, knowsAbout: 1.515, subjectiveCost: 1.59497e+006, positionAccuracy: 0.0134763" 

### run
"Distance: 22.2474, knowsAbout: 0.520926, subjectiveCost: 0.191285, positionAccuracy: 25.4444" 
"Distance: 13.4895, knowsAbout: 1.35, subjectiveCost: 1.296e+006, positionAccuracy: 2.1673" 
"Distance: 12.9786, knowsAbout: 1.515, subjectiveCost: 1.296e+006, positionAccuracy: 0.0417143" 

### sprint
"Distance: 20.9382, knowsAbout: 0.763384, subjectiveCost: 0.223078, positionAccuracy: 23.9631" 
"Distance: 15.5609, knowsAbout: 1.35, subjectiveCost: 1.296e+006, positionAccuracy: 17.8247" 
"Distance: 2.80105, knowsAbout: 1.515, subjectiveCost: 1.59509e+006, positionAccuracy: 0.00897537" 

### crawl - slow
"Distance: 9.44755, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.8045" 

### crawl - normal
"Distance: 12.6016, knowsAbout: 0.287834, subjectiveCost: 0.122481, positionAccuracy: 14.4272" 
"Distance: 11.3799, knowsAbout: 1.515, subjectiveCost: 0.122481, positionAccuracy: 0.0365535" 

### crawl - fast
"Distance: 12.7847, knowsAbout: 0.301143, subjectiveCost: 0.122481, positionAccuracy: 14.6306" 
"Distance: 11.2847, knowsAbout: 1.515, subjectiveCost: 0.122481, positionAccuracy: 0.0362485" 

### crawl - slow - night
"Distance: 9.41852, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.7758" 
Notes
  1. knowsAbout: 1.515 / 1.35 - means the unit has identified you as an hostile enemy
  2. for lower values it has noticed you and tries to face the sound source to check what it is
  3. the unit has a bit of trouble to turn 360° fast at times
  4. so most important is the initial distance the unit picks the player up IMO - not once it has fully identified you as enemy
  5. day vs night seems to make no difference
  6. even with slow crawl it picks you up 9 meters away from behind - this seems too much to me
  7. that said the unit has a lot of trouble to identify you as enemy; most times you can crawl right up to it before it identifies you as enemy
  8. this seems strange too, as on the open ground without grass there is nothing to conceal you / hinder its view and in other movement speeds with crawl, it picks you up a lot quick while it turns

Exp
At least during night times with slow crawl one should be able
to get very very close (1-2m?) to the enemy from behind.

Repro
  1. Launch the attached demo mission in the editor
  2. Use different speed modes when advancing to the enemy from behind

Detailed logging values:

### walk
"Distance: 16.3243, knowsAbout: 0.324038, subjectiveCost: 0.134179, positionAccuracy: 18.6957" 
"Distance: 16.14, knowsAbout: 0.331459, subjectiveCost: 0.134179, positionAccuracy: 18.4853" 
"Distance: 15.9468, knowsAbout: 0.339609, subjectiveCost: 0.134179, positionAccuracy: 18.2621" 
"Distance: 15.7513, knowsAbout: 0.347773, subjectiveCost: 0.134179, positionAccuracy: 18.0465" 
"Distance: 15.5582, knowsAbout: 0.356536, subjectiveCost: 0.134179, positionAccuracy: 17.8233" 
"Distance: 15.3651, knowsAbout: 0.365629, subjectiveCost: 0.134179, positionAccuracy: 17.6003" 
"Distance: 15.1629, knowsAbout: 0.375194, subjectiveCost: 0.134179, positionAccuracy: 17.3745" 
"Distance: 14.963, knowsAbout: 0.385252, subjectiveCost: 0.134179, positionAccuracy: 17.1462" 
"Distance: 14.7654, knowsAbout: 0.395596, subjectiveCost: 0.134179, positionAccuracy: 16.9206" 
"Distance: 14.5587, knowsAbout: 0.406994, subjectiveCost: 0.134179, positionAccuracy: 16.6819" 
"Distance: 14.3612, knowsAbout: 0.418231, subjectiveCost: 0.134179, positionAccuracy: 16.4563" 
"Distance: 14.1456, knowsAbout: 0.430888, subjectiveCost: 0.134179, positionAccuracy: 16.2128" 
"Distance: 13.9435, knowsAbout: 0.44357, subjectiveCost: 0.134179, positionAccuracy: 15.9794" 
"Distance: 13.7346, knowsAbout: 0.456965, subjectiveCost: 0.134179, positionAccuracy: 15.7434" 
"Distance: 13.5191, knowsAbout: 0.47129, subjectiveCost: 0.134179, positionAccuracy: 15.5023" 
"Distance: 13.317, knowsAbout: 0.485962, subjectiveCost: 0.134179, positionAccuracy: 15.2665" 
"Distance: 13.1171, knowsAbout: 0.501004, subjectiveCost: 0.134179, positionAccuracy: 15.0356" 
"Distance: 12.9105, knowsAbout: 0.517105, subjectiveCost: 0.134179, positionAccuracy: 14.7996" 
"Distance: 12.7084, knowsAbout: 0.533617, subjectiveCost: 0.134179, positionAccuracy: 14.5689" 
"Distance: 12.5132, knowsAbout: 0.550333, subjectiveCost: 0.134179, positionAccuracy: 14.3459" 
"Distance: 12.2978, knowsAbout: 0.569904, subjectiveCost: 0.134179, positionAccuracy: 14.0974" 
"Distance: 12.0979, knowsAbout: 0.588603, subjectiveCost: 0.134179, positionAccuracy: 13.8717" 
"Distance: 11.8937, knowsAbout: 0.608449, subjectiveCost: 0.134179, positionAccuracy: 13.6436" 
"Distance: 11.6961, knowsAbout: 0.6298, subjectiveCost: 0.134179, positionAccuracy: 13.4103" 
"Distance: 11.4963, knowsAbout: 0.65155, subjectiveCost: 0.134179, positionAccuracy: 13.1846" 
"Distance: 11.2875, knowsAbout: 0.67523, subjectiveCost: 0.134179, positionAccuracy: 12.9513" 
"Distance: 11.0878, knowsAbout: 0.699656, subjectiveCost: 0.134179, positionAccuracy: 12.7233" 
"Distance: 10.8858, knowsAbout: 0.726339, subjectiveCost: 0.134179, positionAccuracy: 12.4874" 
"Distance: 10.6883, knowsAbout: 0.753308, subjectiveCost: 0.134179, positionAccuracy: 12.2618" 
"Distance: 10.4817, knowsAbout: 0.782478, subjectiveCost: 0.134179, positionAccuracy: 12.0311" 
"Distance: 10.2775, knowsAbout: 0.812664, subjectiveCost: 0.134179, positionAccuracy: 11.8055" 
"Distance: 10.1063, knowsAbout: 0.841734, subjectiveCost: 0.134179, positionAccuracy: 11.5999" 
"Distance: 9.89748, knowsAbout: 0.877445, subjectiveCost: 0.134179, positionAccuracy: 11.3614" 
"Distance: 9.68864, knowsAbout: 0.915064, subjectiveCost: 1.65896e+006, positionAccuracy: 11.1254" 
"Distance: 9.47541, knowsAbout: 0.9375, subjectiveCost: 1.65896e+006, positionAccuracy: 10.8794" 
"Distance: 9.25999, knowsAbout: 0.9375, subjectiveCost: 1.65896e+006, positionAccuracy: 10.6333" 
"Distance: 9.04239, knowsAbout: 0.9375, subjectiveCost: 1.65896e+006, positionAccuracy: 10.3873" 
"Distance: 8.80567, knowsAbout: 0.9375, subjectiveCost: 1.65896e+006, positionAccuracy: 10.1414" 
"Distance: 8.57125, knowsAbout: 0.9375, subjectiveCost: 1.65896e+006, positionAccuracy: 9.85183" 
"Distance: 8.33913, knowsAbout: 0.9375, subjectiveCost: 1.65896e+006, positionAccuracy: 9.58174" 
"Distance: 8.08413, knowsAbout: 0.9375, subjectiveCost: 1.65896e+006, positionAccuracy: 9.31175" 
"Distance: 7.85457, knowsAbout: 0.9375, subjectiveCost: 1.62699e+006, positionAccuracy: 9.03089" 
"Distance: 7.62678, knowsAbout: 0.9375, subjectiveCost: 1.62699e+006, positionAccuracy: 8.77327" 
"Distance: 7.46017, knowsAbout: 0.9375, subjectiveCost: 1.62699e+006, positionAccuracy: 8.58049" 
"Distance: 7.24682, knowsAbout: 0.9375, subjectiveCost: 1.62699e+006, positionAccuracy: 8.33433" 
"Distance: 7.03567, knowsAbout: 0.9375, subjectiveCost: 1.62699e+006, positionAccuracy: 8.09319" 
"Distance: 6.82683, knowsAbout: 0.9375, subjectiveCost: 1.62699e+006, positionAccuracy: 7.85972" 
"Distance: 6.61568, knowsAbout: 0.9375, subjectiveCost: 1.62699e+006, positionAccuracy: 7.61356" 
"Distance: 6.42455, knowsAbout: 0.9375, subjectiveCost: 1.62699e+006, positionAccuracy: 7.40797" 
"Distance: 6.20913, knowsAbout: 0.9375, subjectiveCost: 1.62699e+006, positionAccuracy: 7.15429" 
"Distance: 5.9981, knowsAbout: 0.9375, subjectiveCost: 1.62699e+006, positionAccuracy: 6.9133" 
"Distance: 5.82699, knowsAbout: 0.9375, subjectiveCost: 1.62699e+006, positionAccuracy: 6.71537" 
"Distance: 5.61145, knowsAbout: 0.9375, subjectiveCost: 1.62699e+006, positionAccuracy: 6.47174" 
"Distance: 5.39812, knowsAbout: 0.9375, subjectiveCost: 1.62699e+006, positionAccuracy: 6.22811" 
"Distance: 5.18479, knowsAbout: 0.9375, subjectiveCost: 1.62699e+006, positionAccuracy: 5.97947" 
"Distance: 4.96487, knowsAbout: 0.9375, subjectiveCost: 1.62699e+006, positionAccuracy: 5.73082" 
"Distance: 4.79157, knowsAbout: 0.9375, subjectiveCost: 1.62699e+006, positionAccuracy: 5.54058" 
"Distance: 4.59368, knowsAbout: 0.9375, subjectiveCost: 1.62699e+006, positionAccuracy: 5.31195" 
"Distance: 4.38941, knowsAbout: 0.9375, subjectiveCost: 1.59497e+006, positionAccuracy: 5.07617" 
"Distance: 4.12707, knowsAbout: 1.515, subjectiveCost: 1.59497e+006, positionAccuracy: 0.0134763" 
"Distance: 3.811, knowsAbout: 1.515, subjectiveCost: 1.59497e+006, positionAccuracy: 0.0136284" 
"Distance: 3.58612, knowsAbout: 1.515, subjectiveCost: 1.59497e+006, positionAccuracy: 0.0116973" 
"Distance: 3.37352, knowsAbout: 1.515, subjectiveCost: 1.59497e+006, positionAccuracy: 0.0120785" 
"Distance: 3.15387, knowsAbout: 1.515, subjectiveCost: 1.59497e+006, positionAccuracy: 0.011312" 
"Distance: 2.92318, knowsAbout: 1.515, subjectiveCost: 1.59497e+006, positionAccuracy: 0.0105379" 
"Distance: 2.73251, knowsAbout: 1.515, subjectiveCost: 1.59497e+006, positionAccuracy: 0.00983443" 
"Distance: 2.55737, knowsAbout: 1.515, subjectiveCost: 1.59509e+006, positionAccuracy: 0.00837914" 
"Distance: 2.38229, knowsAbout: 1.515, subjectiveCost: 1.59509e+006, positionAccuracy: 0.00782547" 
"Distance: 2.21179, knowsAbout: 1.515, subjectiveCost: 1.59509e+006, positionAccuracy: 0.00726461" 
"Distance: 2.04356, knowsAbout: 1.515, subjectiveCost: 1.59509e+006, positionAccuracy: 0.00672547" 
"Distance: 1.87094, knowsAbout: 1.515, subjectiveCost: 1.59509e+006, positionAccuracy: 0.00618664" 
"Distance: 1.70283, knowsAbout: 1.515, subjectiveCost: 1.59509e+006, positionAccuracy: 0.00562642" 
"Distance: 1.62427, knowsAbout: 1.515, subjectiveCost: 1.59509e+006, positionAccuracy: 0.00491867" 
"Distance: 1.51633, knowsAbout: 1.515, subjectiveCost: 1.59509e+006, positionAccuracy: 0.00483404" 
"Distance: 1.45614, knowsAbout: 1.515, subjectiveCost: 1.59509e+006, positionAccuracy: 0.00473331" 
"Distance: 1.47417, knowsAbout: 1.515, subjectiveCost: 1.59509e+006, positionAccuracy: 0.00484911" 
"Distance: 1.37005, knowsAbout: 1.515, subjectiveCost: 1.59509e+006, positionAccuracy: 0.00449868" 
"Distance: 1.27632, knowsAbout: 1.515, subjectiveCost: 1.59509e+006, positionAccuracy: 0.00418315" 
"Distance: 1.19954, knowsAbout: 1.515, subjectiveCost: 1.59509e+006, positionAccuracy: 0.0038545" 
"Distance: 1.3536, knowsAbout: 1.515, subjectiveCost: 1.59509e+006, positionAccuracy: 0.00433732" 
"Distance: 1.49837, knowsAbout: 1.515, subjectiveCost: 1.59509e+006, positionAccuracy: 0.00480122" 

### run
"Distance: 22.2474, knowsAbout: 0.520926, subjectiveCost: 0.191285, positionAccuracy: 25.4444" 
"Distance: 21.7165, knowsAbout: 0.546501, subjectiveCost: 0.191285, positionAccuracy: 24.8419" 
"Distance: 21.205, knowsAbout: 0.573315, subjectiveCost: 0.191285, positionAccuracy: 24.254" 
"Distance: 20.7118, knowsAbout: 0.600799, subjectiveCost: 0.191285, positionAccuracy: 23.6928" 
"Distance: 20.1643, knowsAbout: 0.633917, subjectiveCost: 0.191285, positionAccuracy: 23.0656" 
"Distance: 19.6645, knowsAbout: 0.66638, subjectiveCost: 0.191285, positionAccuracy: 22.4967" 
"Distance: 19.1697, knowsAbout: 0.701286, subjectiveCost: 0.191285, positionAccuracy: 21.9297" 
"Distance: 18.6616, knowsAbout: 0.73979, subjectiveCost: 0.191285, positionAccuracy: 21.3514" 
"Distance: 18.1272, knowsAbout: 0.783961, subjectiveCost: 0.191285, positionAccuracy: 20.7412" 
"Distance: 17.624, knowsAbout: 0.829278, subjectiveCost: 0.191285, positionAccuracy: 20.1665" 
"Distance: 17.1129, knowsAbout: 0.879115, subjectiveCost: 0.191285, positionAccuracy: 19.5865" 
"Distance: 16.6015, knowsAbout: 0.933803, subjectiveCost: 0.191285, positionAccuracy: 19.0043" 
"Distance: 16.0802, knowsAbout: 0.995369, subjectiveCost: 0.191285, positionAccuracy: 18.4072" 
"Distance: 15.5755, knowsAbout: 1.06099, subjectiveCost: 0.191285, positionAccuracy: 17.8289" 
"Distance: 15.0643, knowsAbout: 1.13405, subjectiveCost: 0.191285, positionAccuracy: 17.2451" 
"Distance: 14.5234, knowsAbout: 1.21988, subjectiveCost: 0.191285, positionAccuracy: 16.6273" 
"Distance: 14.0123, knowsAbout: 1.30993, subjectiveCost: 1.296e+006, positionAccuracy: 16.0456" 
"Distance: 13.4895, knowsAbout: 1.35, subjectiveCost: 1.296e+006, positionAccuracy: 2.1673" 
"Distance: 12.9786, knowsAbout: 1.515, subjectiveCost: 1.296e+006, positionAccuracy: 0.0417143" 
"Distance: 12.4713, knowsAbout: 1.515, subjectiveCost: 1.296e+006, positionAccuracy: 0.0400835" 
"Distance: 11.9289, knowsAbout: 1.515, subjectiveCost: 1.296e+006, positionAccuracy: 0.0383455" 
"Distance: 11.3815, knowsAbout: 1.515, subjectiveCost: 1.296e+006, positionAccuracy: 0.0402446" 
"Distance: 10.854, knowsAbout: 1.515, subjectiveCost: 1.296e+006, positionAccuracy: 0.0384029" 
"Distance: 10.3362, knowsAbout: 1.515, subjectiveCost: 1.296e+006, positionAccuracy: 0.0365604" 
"Distance: 9.81532, knowsAbout: 1.515, subjectiveCost: 1.296e+006, positionAccuracy: 0.0347304" 
"Distance: 9.281, knowsAbout: 1.515, subjectiveCost: 1.296e+006, positionAccuracy: 0.0328527" 
"Distance: 8.72875, knowsAbout: 1.515, subjectiveCost: 1.65891e+006, positionAccuracy: 0.0309586" 
"Distance: 8.16174, knowsAbout: 1.515, subjectiveCost: 1.65891e+006, positionAccuracy: 0.0290186" 
"Distance: 7.6241, knowsAbout: 1.515, subjectiveCost: 1.65891e+006, positionAccuracy: 0.0271644" 
"Distance: 7.11309, knowsAbout: 1.515, subjectiveCost: 1.65891e+006, positionAccuracy: 0.0252174" 
"Distance: 6.549, knowsAbout: 1.515, subjectiveCost: 1.65891e+006, positionAccuracy: 0.0232584" 
"Distance: 6.02372, knowsAbout: 1.515, subjectiveCost: 1.65891e+006, positionAccuracy: 0.0213872" 
"Distance: 5.68701, knowsAbout: 1.515, subjectiveCost: 1.65891e+006, positionAccuracy: 0.0200451" 
"Distance: 5.68701, knowsAbout: 1.515, subjectiveCost: 1.59509e+006, positionAccuracy: 0.0200451" 

### sprint
"Distance: 20.9382, knowsAbout: 0.763384, subjectiveCost: 0.223078, positionAccuracy: 23.9631" 
"Distance: 20.2521, knowsAbout: 0.81569, subjectiveCost: 0.223078, positionAccuracy: 23.1821" 
"Distance: 19.6003, knowsAbout: 0.870706, subjectiveCost: 0.223078, positionAccuracy: 22.4378" 
"Distance: 18.9163, knowsAbout: 0.934649, subjectiveCost: 0.223078, positionAccuracy: 21.6566" 
"Distance: 18.2732, knowsAbout: 1.00166, subjectiveCost: 1.296e+006, positionAccuracy: 20.9197" 
"Distance: 17.5998, knowsAbout: 1.0793, subjectiveCost: 1.296e+006, positionAccuracy: 20.1532" 
"Distance: 16.9159, knowsAbout: 1.16809, subjectiveCost: 1.296e+006, positionAccuracy: 19.3721" 
"Distance: 16.2362, knowsAbout: 1.26731, subjectiveCost: 1.296e+006, positionAccuracy: 18.5983" 
"Distance: 15.5609, knowsAbout: 1.35, subjectiveCost: 1.296e+006, positionAccuracy: 17.8247" 
"Distance: 14.9223, knowsAbout: 1.35, subjectiveCost: 1.296e+006, positionAccuracy: 17.0978" 
"Distance: 14.275, knowsAbout: 1.35, subjectiveCost: 1.296e+006, positionAccuracy: 16.366" 
"Distance: 13.6149, knowsAbout: 1.35, subjectiveCost: 1.296e+006, positionAccuracy: 15.6072" 
"Distance: 12.9604, knowsAbout: 1.35, subjectiveCost: 1.296e+006, positionAccuracy: 14.855" 
"Distance: 12.3019, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 14.1052" 
"Distance: 11.6219, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 13.3287" 
"Distance: 10.9511, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 12.5626" 
"Distance: 10.276, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 11.7942" 
"Distance: 9.60766, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 11.0284" 
"Distance: 8.9292, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 10.2561" 
"Distance: 8.25977, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 9.49155" 
"Distance: 7.59276, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 8.72978" 
"Distance: 6.93518, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 7.97877" 
"Distance: 6.28091, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 7.23151" 
"Distance: 5.6215, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 6.47586" 
"Distance: 4.95571, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 5.71785" 
"Distance: 4.27683, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 4.95449" 
"Distance: 3.644, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 4.2217" 
"Distance: 2.99462, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 3.47481" 
"Distance: 2.34353, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 2.73494" 
"Distance: 1.70494, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 2.00099" 
"Distance: 1.12046, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 1.32805" 
"Distance: 0.844342, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 0.892207" 
"Distance: 0.978201, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 0.892207" 
"Distance: 1.35302, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 0.892207" 
"Distance: 1.9, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 0.892207" 
"Distance: 2.51452, knowsAbout: 1.35, subjectiveCost: 1.59509e+006, positionAccuracy: 0.34932" 
"Distance: 2.80105, knowsAbout: 1.515, subjectiveCost: 1.59509e+006, positionAccuracy: 0.00897537" 
"Distance: 2.80105, knowsAbout: 1.515, subjectiveCost: 1.59509e+006, positionAccuracy: 0.0098729" 

### crawl - slow
"Distance: 9.44755, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.8045" 
"Distance: 9.38998, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.7394" 
"Distance: 9.33314, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.6745" 
"Distance: 9.27617, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.6088" 
"Distance: 9.21799, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.543" 
"Distance: 9.15835, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.4758" 
"Distance: 9.10151, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.4109" 
"Distance: 9.04053, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.3404" 
"Distance: 8.98101, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.2739" 
"Distance: 8.92076, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.2051" 
"Distance: 8.8599, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.1349" 
"Distance: 8.7977, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.0646" 
"Distance: 8.73672, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.99578" 
"Distance: 8.67525, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.92475" 
"Distance: 8.615, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.85525" 
"Distance: 8.55403, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.78562" 

### crawl - normal
"Distance: 12.6016, knowsAbout: 0.287834, subjectiveCost: 0.122481, positionAccuracy: 14.4272" 
"Distance: 12.5081, knowsAbout: 0.292318, subjectiveCost: 0.122481, positionAccuracy: 14.3161" 
"Distance: 12.3968, knowsAbout: 0.29362, subjectiveCost: 0.122481, positionAccuracy: 14.1904" 
"Distance: 12.2855, knowsAbout: 0.29362, subjectiveCost: 0.122481, positionAccuracy: 14.0619" 
"Distance: 12.1628, knowsAbout: 0.298608, subjectiveCost: 0.122481, positionAccuracy: 13.9204" 
"Distance: 12.0452, knowsAbout: 0.304395, subjectiveCost: 0.122481, positionAccuracy: 13.7874" 
"Distance: 11.9299, knowsAbout: 0.335553, subjectiveCost: 0.122481, positionAccuracy: 13.6631" 
"Distance: 11.8377, knowsAbout: 0.341225, subjectiveCost: 0.122481, positionAccuracy: 13.5491" 
"Distance: 11.7264, knowsAbout: 0.347646, subjectiveCost: 0.122481, positionAccuracy: 13.4234" 
"Distance: 11.6114, knowsAbout: 0.354474, subjectiveCost: 0.122481, positionAccuracy: 13.2935" 
"Distance: 11.4924, knowsAbout: 0.361911, subjectiveCost: 0.122481, positionAccuracy: 13.1562" 
"Distance: 11.3799, knowsAbout: 1.515, subjectiveCost: 0.122481, positionAccuracy: 0.0365535" 
"Distance: 11.2635, knowsAbout: 1.515, subjectiveCost: 0.122481, positionAccuracy: 0.0361808" 
"Distance: 11.0941, knowsAbout: 1.515, subjectiveCost: 0.122481, positionAccuracy: 0.035731" 
"Distance: 11.017, knowsAbout: 1.515, subjectiveCost: 0.122481, positionAccuracy: 0.0354272" 
"Distance: 10.917, knowsAbout: 1.515, subjectiveCost: 0.122481, positionAccuracy: 0.0350744" 
"Distance: 10.7906, knowsAbout: 1.515, subjectiveCost: 0.122481, positionAccuracy: 0.0347788" 
"Distance: 10.6717, knowsAbout: 1.515, subjectiveCost: 0.122481, positionAccuracy: 0.0347788" 
"Distance: 10.5502, knowsAbout: 1.515, subjectiveCost: 0.122481, positionAccuracy: 0.0347788" 
"Distance: 10.4148, knowsAbout: 1.515, subjectiveCost: 1.659e+006, positionAccuracy: 0.033518" 
"Distance: 10.32, knowsAbout: 1.515, subjectiveCost: 1.659e+006, positionAccuracy: 0.0331695" 
"Distance: 10.1609, knowsAbout: 1.515, subjectiveCost: 1.659e+006, positionAccuracy: 0.0360494" 
"Distance: 10.0246, knowsAbout: 1.515, subjectiveCost: 1.659e+006, positionAccuracy: 0.0355733" 
"Distance: 9.887, knowsAbout: 1.515, subjectiveCost: 1.659e+006, positionAccuracy: 0.0350979" 
"Distance: 9.67619, knowsAbout: 1.515, subjectiveCost: 1.659e+006, positionAccuracy: 0.0343595" 
"Distance: 9.49332, knowsAbout: 1.515, subjectiveCost: 1.659e+006, positionAccuracy: 0.0337233" 
"Distance: 9.33801, knowsAbout: 1.515, subjectiveCost: 1.659e+006, positionAccuracy: 0.0332342" 
"Distance: 9.23823, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0326868" 
"Distance: 9.11307, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.032268" 
"Distance: 8.99938, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0318583" 
"Distance: 8.89081, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0314666" 
"Distance: 8.73285, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0309635" 
"Distance: 8.63173, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0305357" 
"Distance: 8.53318, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0301974" 
"Distance: 8.42462, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0298234" 
"Distance: 8.32228, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0294493" 
"Distance: 8.28947, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.029218" 
"Distance: 8.28947, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.029218" 
"Distance: 8.28947, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.029218" 
"Distance: 8.28947, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.029218" 
"Distance: 8.28947, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.029218" 
"Distance: 8.28947, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0265618" 
"Distance: 8.28947, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0265618" 
"Distance: 8.28947, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0265618" 
"Distance: 8.28947, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0265618" 
"Distance: 8.28947, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0265618" 
"Distance: 8.28947, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0265618" 
"Distance: 8.28947, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0265618" 
"Distance: 8.28947, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0265618" 
"Distance: 8.28947, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0265618" 
"Distance: 8.28947, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0265618" 
"Distance: 8.28947, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0265618" 
"Distance: 8.28947, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0265618" 
"Distance: 8.28947, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0265618" 

### crawl - fast
"Distance: 12.7847, knowsAbout: 0.301143, subjectiveCost: 0.122481, positionAccuracy: 14.6306" 
"Distance: 12.6758, knowsAbout: 0.306269, subjectiveCost: 0.122481, positionAccuracy: 14.5077" 
"Distance: 12.5607, knowsAbout: 0.311707, subjectiveCost: 0.122481, positionAccuracy: 14.3806" 
"Distance: 12.4393, knowsAbout: 0.31787, subjectiveCost: 0.122481, positionAccuracy: 14.2405" 
"Distance: 12.3268, knowsAbout: 0.323821, subjectiveCost: 0.122481, positionAccuracy: 14.109" 
"Distance: 12.208, knowsAbout: 0.329933, subjectiveCost: 0.122481, positionAccuracy: 13.9777" 
"Distance: 12.0879, knowsAbout: 0.336715, subjectiveCost: 0.122481, positionAccuracy: 13.8363" 
"Distance: 11.9766, knowsAbout: 0.342918, subjectiveCost: 0.122481, positionAccuracy: 13.7105" 
"Distance: 11.8603, knowsAbout: 0.349661, subjectiveCost: 0.122481, positionAccuracy: 13.5777" 
"Distance: 11.7438, knowsAbout: 0.356686, subjectiveCost: 0.122481, positionAccuracy: 13.4433" 
"Distance: 11.6313, knowsAbout: 0.360157, subjectiveCost: 0.122481, positionAccuracy: 13.3134" 
"Distance: 11.5212, knowsAbout: 0.360157, subjectiveCost: 0.122481, positionAccuracy: 13.1905" 
"Distance: 11.3998, knowsAbout: 0.360157, subjectiveCost: 0.122481, positionAccuracy: 13.0504" 
"Distance: 11.2847, knowsAbout: 1.515, subjectiveCost: 0.122481, positionAccuracy: 0.0362485" 
"Distance: 11.1683, knowsAbout: 1.515, subjectiveCost: 0.122481, positionAccuracy: 0.0358837" 
"Distance: 11.0633, knowsAbout: 1.515, subjectiveCost: 1.659e+006, positionAccuracy: 0.0355716" 
"Distance: 10.9647, knowsAbout: 1.515, subjectiveCost: 1.659e+006, positionAccuracy: 0.0352271" 
"Distance: 10.8446, knowsAbout: 1.515, subjectiveCost: 1.659e+006, positionAccuracy: 0.0348505" 
"Distance: 10.7472, knowsAbout: 1.515, subjectiveCost: 1.659e+006, positionAccuracy: 0.0345423" 
"Distance: 10.6536, knowsAbout: 1.515, subjectiveCost: 1.659e+006, positionAccuracy: 0.0342302" 
"Distance: 10.5323, knowsAbout: 1.515, subjectiveCost: 1.659e+006, positionAccuracy: 0.0338497" 
"Distance: 10.416, knowsAbout: 1.515, subjectiveCost: 1.659e+006, positionAccuracy: 0.0334688" 
"Distance: 10.2984, knowsAbout: 1.515, subjectiveCost: 1.659e+006, positionAccuracy: 0.0330922" 
"Distance: 10.1808, knowsAbout: 1.515, subjectiveCost: 1.659e+006, positionAccuracy: 0.0327113" 
"Distance: 10.0607, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0355683" 
"Distance: 9.87024, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0350303" 
"Distance: 9.70979, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0343266" 
"Distance: 9.54682, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0337569" 
"Distance: 9.34871, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0331959" 
"Distance: 9.19719, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0325332" 
"Distance: 9.10363, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0321948" 
"Distance: 9.00641, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0318607" 
"Distance: 8.91285, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0315223" 
"Distance: 8.78769, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0310812" 
"Distance: 8.66133, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0306358" 
"Distance: 8.53496, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0301947" 
"Distance: 8.43653, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.029852" 
"Distance: 8.3442, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.029518" 
"Distance: 8.2215, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0290898" 
"Distance: 8.12552, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0287515" 
"Distance: 8.02953, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0284132" 
"Distance: 7.90196, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0279678" 
"Distance: 7.80964, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0276338" 
"Distance: 7.68708, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0271971" 
"Distance: 7.65805, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0245386" 
"Distance: 7.65805, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0245386" 
"Distance: 7.65805, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0245386" 
"Distance: 7.65805, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0245386" 
"Distance: 7.65805, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0245386" 
"Distance: 7.65805, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0269925" 
"Distance: 7.65805, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0245386" 
"Distance: 7.65805, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0245386" 
"Distance: 7.65805, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0245386" 
"Distance: 7.65805, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0245386" 
"Distance: 7.65805, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0245386" 
"Distance: 7.65805, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0245386" 
"Distance: 7.65805, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0245386" 
"Distance: 7.65805, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0245386" 
"Distance: 7.65805, knowsAbout: 1.515, subjectiveCost: 1.62705e+006, positionAccuracy: 0.0245386" 

### crawl - slow - night
"Distance: 9.41852, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.7758" 
"Distance: 9.36583, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.7156" 
"Distance: 9.31691, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.6584" 
"Distance: 9.24471, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.5858" 
"Distance: 9.19397, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.5187" 
"Distance: 9.14262, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.46" 
"Distance: 9.06309, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.3707" 
"Distance: 9.0104, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.3106" 
"Distance: 8.95771, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.2504" 
"Distance: 8.90027, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.1855" 
"Distance: 8.84685, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.1229" 
"Distance: 8.7955, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.0643" 
"Distance: 8.74282, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.0041" 
"Distance: 8.68879, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.94397" 
"Distance: 8.59464, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.84564" 
"Distance: 8.53256, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.76556" 
"Distance: 8.47512, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.7008" 
"Distance: 8.41976, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.63604" 
"Distance: 8.36781, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.57588" 
"Distance: 8.31366, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.51488" 
"Distance: 8.25695, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.45165" 
"Distance: 8.20159, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.38758" 
"Distance: 8.14415, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.32129" 
"Distance: 8.09147, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.26113" 
"Distance: 8.03952, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.20097" 
"Distance: 7.98477, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.13928" 
"Distance: 7.93075, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.07828" 
"Distance: 7.87673, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.01506" 
"Distance: 7.82198, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.95337" 
"Distance: 7.7693, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.89321" 
"Distance: 7.71516, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.83138" 
"Distance: 7.6598, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.76886" 
"Distance: 7.60713, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.70717" 
"Distance: 7.55238, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.64702" 
"Distance: 7.493, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.57837" 
"Distance: 7.44106, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.51752" 
"Distance: 7.38571, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.45584" 
"Distance: 7.32902, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.3911" 
"Distance: 7.27769, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.33095" 
"Distance: 7.22234, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.26927" 
"Distance: 7.16638, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.20537" 
"Distance: 7.11225, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.14285" 
"Distance: 7.05825, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.08034" 
"Distance: 7.00351, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.01867" 
"Distance: 6.95085, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.95853" 
"Distance: 6.89478, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.89602" 
"Distance: 6.83675, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.82892" 
"Distance: 6.78202, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.76642" 
"Distance: 6.724, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.70252" 
"Distance: 6.65855, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.62777" 
"Distance: 6.5998, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.55915" 
"Distance: 6.5458, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.49512" 
"Distance: 6.49047, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.43346" 
"Distance: 6.43514, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.37027" 
"Distance: 6.37774, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.30555" 
"Distance: 6.32034, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.23917" 
"Distance: 6.24088, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.14773" 
"Distance: 6.1869, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.08678" 
"Distance: 6.13364, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.02443" 
"Distance: 6.07832, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.96278" 
"Distance: 6.02374, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.90197" 
"Distance: 5.96172, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.82962" 
"Distance: 5.90713, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.76728" 
"Distance: 5.85121, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.70342" 
"Distance: 5.79456, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.63872" 
"Distance: 5.73389, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.57096" 
"Distance: 5.67919, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.50697" 
"Distance: 5.62389, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.44381" 
"Distance: 5.56651, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.37829" 
"Distance: 5.51243, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.31583" 
"Distance: 5.45835, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.25407" 
"Distance: 5.40306, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.19092" 
"Distance: 5.34838, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.12917" 
"Distance: 5.28505, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.0599" 
"Distance: 5.22842, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.99218" 
"Distance: 5.1718, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.92834" 
"Distance: 5.11384, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.86368" 
"Distance: 5.05321, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.79138" 
"Distance: 4.99927, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.73048" 
"Distance: 4.94461, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.66736" 
"Distance: 4.88934, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.60494" 
"Distance: 4.83468, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.54182" 
"Distance: 4.7821, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.48177" 
"Distance: 4.72685, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.41867" 
"Distance: 4.66831, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.35404" 
"Distance: 4.61172, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.28788" 
"Distance: 4.55854, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.22563" 
"Distance: 4.50184, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.16323" 
"Distance: 4.44065, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.09557" 
"Distance: 4.38201, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.02555" 
"Distance: 4.32666, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 4.96164" 
"Distance: 4.27071, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 4.89927" 
"Distance: 4.21476, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 4.83385" 
"Distance: 4.16028, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 4.77232" 
"Distance: 4.10446, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 4.70857" 
"Distance: 4.04914, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 4.6447" 
"Distance: 3.99054, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 4.5793" 
"Distance: 3.93669, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 4.51697" 
"Distance: 3.88211, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 4.45395" 
"Distance: 3.82694, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 4.39163" 
"Distance: 3.76242, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 4.32099" 
"Distance: 3.70847, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 4.25564" 
"Distance: 3.65332, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 4.19334" 
"Distance: 3.59684, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 4.12884" 
"Distance: 3.54438, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 4.0674" 
"Distance: 3.49059, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 4.0068" 
"Distance: 3.43741, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 3.94607" 
"Distance: 3.35221, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 3.85181" 
"Distance: 3.29566, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 3.78418" 
"Distance: 3.23998, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 3.72128" 
"Distance: 3.18613, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 3.65908" 
"Distance: 3.12901, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 3.59537" 
"Distance: 3.07191, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 3.52933" 
"Distance: 3.01688, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 3.46648" 
"Distance: 2.96115, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 3.40365" 
"Distance: 2.90215, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 3.33544" 
"Distance: 2.84923, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 3.275" 
"Distance: 2.79621, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 3.21292" 
"Distance: 2.74066, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 3.151" 
"Distance: 2.68102, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 3.08523" 
"Distance: 2.62552, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 3.01949" 
"Distance: 2.56798, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 2.95377" 
"Distance: 2.5118, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 2.89043" 
"Distance: 2.44695, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 2.81939" 
"Distance: 2.3895, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 2.74992" 
"Distance: 2.3895, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 2.72883" 
"Distance: 2.3895, knowsAbout: 0.282191, subjectiveCost: 0.11962, positionAccuracy: 2.72883" 

AIcanHearEvenSlowMovement.Desert_E.7z (1.4 kB) kju, 08/10/2011 09:29


Related issues

related to ARMA2 Community Issue Tracker - Feature #18956: Improve perceived position design for AI infantry Assigned 04/16/2011
related to ARMA2 Community Issue Tracker - Feature #24408: Questions on CfgAISkill and setSkill array Assigned 09/11/2011
related to ARMA2 Community Issue Tracker - Bug #23301: AI is unable to pointpoint sound source (well) Duplicate 08/10/2011 11/01/2011
related to ARMA2 Community Issue Tracker - Bug #28022: AI fixates on perceived source of gunshot, does not adjus... Assigned 01/20/2012
related to ARMA2 Community Issue Tracker - Bug #28401: AI gets aware of friendly units which are in different gr... Assigned 02/04/2012

History

Updated by kju almost 4 years ago

  • Description updated (diff)

Updated by kju almost 4 years ago

In addition it seems unit skill has very little influence:

### crawl - slow - 100% unit skill
"Distance: 9.44755, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.8045" 

### crawl - slow - 100% unit skill - night
"Distance: 9.41852, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.7758" 

### crawl - slow - 50% unit skill
"Distance: 9.05784, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.7978" 
"Distance: 4.1211, knowsAbout: 1.515, subjectiveCost: 0.121022, positionAccuracy: 0.0157282" 

### crawl - slow - 0% unit skill
"Distance: 8.55695, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.6769" 
"Distance: 4.70725, knowsAbout: 1.515, subjectiveCost: 0.121022, positionAccuracy: 0.0215143" 

Unless difficulty enemy skill overwrites unit skill?!
It would be great to insights how unit skill, difficulty skill and setSkill array are connected.


Detailed logging values:

### crawl - slow - 50% unit skill
"Distance: 9.05784, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.7978" 
"Distance: 8.99625, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.7268" 
"Distance: 8.94075, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.6591" 
"Distance: 8.87916, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.5874" 
"Distance: 8.82026, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.5166" 
"Distance: 8.76001, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.4456" 
"Distance: 8.69964, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.373" 
"Distance: 8.63805, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.2997" 
"Distance: 8.57646, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.2287" 
"Distance: 8.5128, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.1522" 
"Distance: 8.45317, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.0787" 
"Distance: 8.39231, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.0072" 
"Distance: 8.33341, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.93778" 
"Distance: 8.27256, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.86461" 
"Distance: 8.20365, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.7826" 
"Distance: 8.14207, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.71002" 
"Distance: 8.08122, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.63758" 
"Distance: 8.02037, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.56515" 
"Distance: 7.95818, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.49112" 
"Distance: 7.89733, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.41869" 
"Distance: 7.83648, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.34626" 
"Distance: 7.77612, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.27369" 
"Distance: 7.71515, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.20112" 
"Distance: 7.65224, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.12695" 
"Distance: 7.592, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.05525" 
"Distance: 7.53104, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.98196" 
"Distance: 7.468, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.90693" 
"Distance: 7.4085, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.83683" 
"Distance: 7.34632, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.76369" 
"Distance: 7.28402, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.68793" 
"Distance: 7.22514, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.61697" 
"Distance: 7.16625, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.54775" 
"Distance: 7.10737, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.47766" 
"Distance: 7.04434, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.40423" 
"Distance: 6.98973, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.34227" 
"Distance: 6.94219, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.28103" 
"Distance: 6.88063, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.20776" 
"Distance: 6.82041, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.1368" 
"Distance: 6.7608, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.06585" 
"Distance: 6.68999, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.98634" 
"Distance: 6.6366, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.92279" 
"Distance: 6.58248, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.85446" 
"Distance: 6.52166, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.7796" 
"Distance: 6.45877, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.70633" 
"Distance: 6.39516, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.63148" 
"Distance: 6.333, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.55749" 
"Distance: 6.27268, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.48409" 
"Distance: 6.2098, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.40924" 
"Distance: 6.14692, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.33599" 
"Distance: 6.08404, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.26115" 
"Distance: 6.02105, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.18616" 
"Distance: 5.97024, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.12568" 
"Distance: 5.9081, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.05085" 
"Distance: 5.8473, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.97848" 
"Distance: 5.78371, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.90365" 
"Distance: 5.73242, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.84332" 
"Distance: 5.67029, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.76777" 
"Distance: 5.59415, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.69542" 
"Distance: 5.52933, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.62145" 
"Distance: 5.48461, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.55546" 
"Distance: 5.43516, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.48629" 
"Distance: 5.35293, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.40596" 
"Distance: 5.28884, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.3217" 
"Distance: 5.23611, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.25182" 
"Distance: 5.16816, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.17094" 
"Distance: 5.10606, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.09615" 
"Distance: 5.04251, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.02049" 
"Distance: 4.97968, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.94658" 
"Distance: 4.91687, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.87094" 
"Distance: 4.85551, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.79791" 
"Distance: 4.79404, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.72401" 
"Distance: 4.73124, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.65084" 
"Distance: 4.67172, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.57913" 
"Distance: 4.611, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.50685" 
"Distance: 4.54882, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.4321" 
"Distance: 4.48664, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.35969" 
"Distance: 4.42459, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.28496" 
"Distance: 4.36182, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.21023" 
"Distance: 4.30183, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.14434" 
"Distance: 4.25245, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.08164" 
"Distance: 4.18969, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.00621" 
"Distance: 4.1211, knowsAbout: 1.515, subjectiveCost: 0.121022, positionAccuracy: 0.0157282" 

### crawl - slow - 0% unit skill
"Distance: 8.55695, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.6769" 
"Distance: 8.49732, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.6036" 
"Distance: 8.43842, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.5309" 
"Distance: 8.37817, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.4551" 
"Distance: 8.3172, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.3792" 
"Distance: 8.25707, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.305" 
"Distance: 8.19817, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.2317" 
"Distance: 8.1372, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.155" 
"Distance: 8.07488, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.0773" 
"Distance: 8.01464, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 10.003" 
"Distance: 7.95245, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.92558" 
"Distance: 7.89148, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.84886" 
"Distance: 7.82978, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.772" 
"Distance: 7.76881, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.69681" 
"Distance: 7.70919, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.62178" 
"Distance: 7.65029, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.54841" 
"Distance: 7.58945, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.47429" 
"Distance: 7.52909, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.39911" 
"Distance: 7.46886, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.32316" 
"Distance: 7.40656, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.24479" 
"Distance: 7.34572, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.16976" 
"Distance: 7.28415, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.09398" 
"Distance: 7.22319, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 9.01637" 
"Distance: 7.16163, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.93968" 
"Distance: 7.10201, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.86541" 
"Distance: 7.04118, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.79039" 
"Distance: 6.98096, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.7137" 
"Distance: 6.92135, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.64036" 
"Distance: 6.8604, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.5661" 
"Distance: 6.79884, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.48851" 
"Distance: 6.73656, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.41016" 
"Distance: 6.67988, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.34532" 
"Distance: 6.63307, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.282" 
"Distance: 6.56823, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.20123" 
"Distance: 6.5068, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.12471" 
"Distance: 6.44598, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 8.04895" 
"Distance: 6.3831, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.97061" 
"Distance: 6.3229, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.89485" 
"Distance: 6.2633, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.82062" 
"Distance: 6.2031, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.74639" 
"Distance: 6.13962, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.6673" 
"Distance: 6.07808, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.58988" 
"Distance: 6.01533, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.51247" 
"Distance: 5.9538, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.43582" 
"Distance: 5.89093, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.3575" 
"Distance: 5.82952, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.28101" 
"Distance: 5.76154, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.19724" 
"Distance: 5.69941, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.11893" 
"Distance: 5.63656, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 7.04063" 
"Distance: 5.57504, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.96324" 
"Distance: 5.5128, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.88737" 
"Distance: 5.45068, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.80908" 
"Distance: 5.38784, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.73079" 
"Distance: 5.32499, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.6525" 
"Distance: 5.26155, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.57437" 
"Distance: 5.20005, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.49686" 
"Distance: 5.14879, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.43467" 
"Distance: 5.08742, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.35655" 
"Distance: 5.02593, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.28087" 
"Distance: 4.96238, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.20003" 
"Distance: 4.90018, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.12254" 
"Distance: 4.83736, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 6.04596" 
"Distance: 4.77663, knowsAbout: 0.282191, subjectiveCost: 0.121022, positionAccuracy: 5.96939" 
"Distance: 4.70725, knowsAbout: 1.515, subjectiveCost: 0.121022, positionAccuracy: 0.0215143" 

Updated by kju almost 4 years ago

  • Description updated (diff)

Updated by Fireball almost 4 years ago

  • Status changed from New to Assigned

Updated by Varanon over 3 years ago

They also hear a silenced shot from an assault rifle over a distance of 500 m. This does not happen with 1.59.

Strike that, also happens in 1.59

Updated by kraze over 3 years ago

In OFP AI was close to being literally blind and deaf at night. I remember crawling 1 meter behind AI - and it didn't notice me.
So OFP shouldn't be used as an example.

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