Evolutionary Robotics Evolutionary Robotics for Swarms
Example: Controllers for a Robot Swarm Design a controller to be placed into a swarm of Unmanned Aerial Vehicles, such that they swarm: Separation: steer to avoid crowding local flockmates Alignment: steer towards the average heading of local flockmates Cohesion: steer to move toward the average position of local flockmates Evolutionary Robotics Evolutionary Robotics for Swarms
Example: Controllers for a Robot Swarm Design a controller to be placed into a swarm of Unmanned Aerial Vehicles, such that they swarm: Evolutionary Robotics Evolutionary Robotics for Swarms
Evolutionary Robotics Evolutionary Robotics for Swarms Question: What tasks cannot be solved by a single robot? Answer:Group hunting
Evolutionary Robotics Evolutionary Robotics for Swarms Question: Can we evolve behaviors for a team of predators? How? Will they evolve to cooperate? Luke, S., Spector, L. (1996) Evolving teamwork and coordination with genetic programming. In Procs. of the First Annual Conference on Genetic Programming, pp
Evolutionary Robotics Evolutionary Robotics for Swarms Luke, S., Spector, L. (1996) Evolving teamwork and coordination with genetic programming. In Procs. of the First Annual Conference on Genetic Programming, pp units G L2 L3 L1 L4 G = gazelle L1 = lion 1 L2 = lion 2 L3 = lion 3 L4 = lion 4
Evolutionary Robotics Evolutionary Robotics for Swarms Luke, S., Spector, L. (1996) Evolving teamwork and coordination with genetic programming. In Procs. of the First Annual Conference on Genetic Programming, pp G(t) L2 L3 L1 L4 Savannah is toroidal: Sensing and moving beyond the edge “wraps around” to the opposing side. G(t+1)L4 sensing moving
Evolutionary Robotics Evolutionary Robotics for Swarms Luke, S., Spector, L. (1996) Evolving teamwork and coordination with genetic programming. In Procs. of the First Annual Conference on Genetic Programming, pp G(t) L2 L3 L1 L4 Gazelle’s behavior b: sensing ||max|| = sqrt( (w/2) 2 + (h/2) 2 ) b = - (v/||v||) (||max|| - ||v||) vVvV
Lion’s behavior L i : Encoded as a tree that operates on 2D vectors: Luke, S., Spector, L. (1996) Evolving teamwork and coordination with genetic programming. In Procs. of the First Annual Conference on Genetic Programming, pp Q: If you were a single lion chasing the gazelle, what is the best strategy?
Lion’s behavior L i : Encoded as a tree that operates on 2D vectors: Luke, S., Spector, L. (1996) Evolving teamwork and coordination with genetic programming. In Procs. of the First Annual Conference on Genetic Programming, pp Q: If you had these additional four sensors, what is the best strategy? + rand-dirgazelle
Lion’s behavior L i : Encoded as a tree that operates on 2D vectors: Luke, S., Spector, L. (1996) Evolving teamwork and coordination with genetic programming. In Procs. of the First Annual Conference on Genetic Programming, pp Q: If you had these additional four sensors, what is the best strategy?
Q: How to evolve teams?Three possible ways: L L1L2L3L4 1. Cloning 2. Free breeding L2L3 L4L1 L2L3 L4L1 L2L3 L4L1 L2L3 L4L1 L2L3 L4L1 L2L3 L4L1 L2L3 L4L1 L2L3 L4L1... L4 3. Restricted breeding
Results: 1200 Evolutionary runs 100 runs for each of three sensing capabilties and three team-construction methods 100 runs: One lion with evolved behavior 100 runs: One randomly-moving lion 100 runs: Four randomly-moving lions 51 generations, population size = 500, max tree size = 70, max tree depth = 17, For each new tree: created by crossover = 90% probability created by mutation = 10% probability For each team evaluation:Place gazelle, lions, randomly Each moves 15 times. Fitness function:Fitness = 0: lion <=1 unit from gazelle Fitness =||nearest lion – gazelle|| - 1: otherwise
Observations: 1. One evolved lion doesn’t do much better than a random lion 2. Four lions do better than one lion (random or evolved) 3. For clones, name-based sensing was worse than deictic sensing; why? 4. For restricted breed, name-based sensing was best; why? Q: What else besides distance to Lion i might a lion want to know?