EXIT = Way Out

Julian Dymacek

April 29

Escape Panic Paper• Dr. Dirk Helbing, Illes J. Farkas, Dr. Tamas

Vicsek• Point mass simulation• Uses psychological forces to keep agents apart and

away from walls• Uses friction to simulate the clogs in front of

doors• Found a combination of rushing to doors and

following neighbors demonstrated escape panic

Craig Reynolds

• Craig Reynolds – Boids– Separation, Alignment, Cohesion

• Craig Reynolds – Steering Behaviors– Obstacle avoidance– Wandering– Following

Wander Behavior

What do I want to do?

• Reproduce the escape panic simulation

• Allow agents to be controlled by behaviors not included in the escape panic paper

• Find behaviors that help agents quickly exit from a room

Behaviors

• Closest– Distance to door/ max distance

• Follow your neighbors– Density of surrounding agents (agent area/ circle area)

• Go with the flow– Avg speed of agents in radius no return/ max speed

• Popularity– Density of agents around door (agent area/ half circle area)

Chromosome for GA

• Each behavior is a 5 bit gene

• Wander is the default behavior

• Another 5 bit gene represents the order of applying behaviors

• A final 5 bit gene encodes desired speed

• 30 total bits

Tests

• Solved for best strategy with a single agent and multiple agents

• Varied the percentage of agents who follow neighbors with 95%, 75%, 50%, 25% and 0%

• Used two separate distributions of agents• Agents had 20 seconds to escape• Fitness was 1-(time to escape/ 20)

Results

• The Good– Found ways besides go to closest

• The Bad– Mostly found go to closest

• The Ugly– The multi-agent tests could become inflated

The Good

Speed Closest Density Flow Friends Order Fitness

100% S 0.516129 0.322581 0.677419 0.322581 0.677419 11(2431) 0.700000

100% C 0.548387 0.322581 0.677419 0.322581 0.677419 10(2413) 0.666667

25% C 0.677419 0.322581 0.677419 0.322581 0.677419 10(2413) 0.700000

5% S 0.677419 0.322581 0.677419 0.838710 0.677419 10(2413) 0.700000

The Bad

Speed Closest Density Flow Friends Order Fitness

50% S 0.451613 0.935484 0.064516 0.677419 0.322581 21(4231) 0.600000

100% C 0.677419 0.322581 0.161290 0.838710 0.677419 10(2431) 0.533333

5% C 0.516129 0.903226 0.290323 0.225806 0.322581 29(1234) 0.666667

25% S 0.838710 0.870968 0.322581 0.677419 0.322581 19(4132) 0.633333

The Ugly

• Since multi-agents were spread throughout the clump they influenced the other “dumb” agents in ways which enabled them to get out faster

• Clumps of evolving agents together form a small pack which can increase exit speed by not getting trapped behind other agents

• Usually got out under 6 seconds

Comments and Future

• Hard to debug and figure how multi-agents respond

• Sheep herding (aren’t we all just sheep) encouraging people exiting stadiums

• More complex environments/ distributions

• One final example/moral

Questions, Comments, Cries of Joy?