Talking Helps: Evolving Communicating Agents for the Predator-Prey Pursuit Problem

We analyze a general model of multi-agent communication in which all agents communicate simultaneously to a message board. A genetic algorithm is used to evolve multi-agent languages for the predator agents in a version of the predator-prey pursuit problem. We show that the resulting behavior of the communicating multi-agent system is equivalent to that of a Mealy nite state machine whose states are determined by the agents' usage of the evolved language. Simulations show that the evolution of a communication language improves the performance of the predators. Increasing the language size (and thus increasing the number of possible states in the Mealy machine) improves the performance even further. Furthermore, the evolved communicating predators perform signi cantly better than all previous work on similar prey. We introduce a method for incrementally increasing the language size, which results in an effective coarse-to- ne search that signi cantly reduces the evolution time requ...

• Type: Journal
• Year: 2000
• Where: ALIFE
• Authors: Kam-Chuen Jim, C. Lee Giles
• Keywords: ALIFE 2000, ALIFE 2007, Language Size, Mealy Machines, Multi-agent