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EXIT = Way Out PowerPoint Presentation
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EXIT = Way Out

EXIT = Way Out

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EXIT = Way Out

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  1. EXIT = Way Out Julian Dymacek April 29

  2. 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

  3. Craig Reynolds • Craig Reynolds – Boids • Separation, Alignment, Cohesion • Craig Reynolds – Steering Behaviors • Obstacle avoidance • Wandering • Following

  4. Wander Behavior

  5. 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

  6. 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)

  7. 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

  8. 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)

  9. 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

  10. The Good

  11. The Bad

  12. 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

  13. 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

  14. Questions, Comments, Cries of Joy?