Learning in a multiagent system is a challenging problem due to two key factors. First, if other agents are simultaneously learning then the environment is no longer stationary, t...
Abstract- We present a concept for developing cooperative characters (agents) for computer games that combines coaching by a human with evolutionary learning. The basic idea is to ...
Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...
Chongjie Zhang, Victor R. Lesser, Sherief Abdallah
An interesting problem which has been widely investigated is under what circumstances will a society of rational agents realize some particular stable situations, and whether they ...
A coevolutionary competitive learning environment for two antagonistic agents is presented. The agents are controlled by a new kind of computational network based on a compartment...
Gul Muhammad Khan, Julian Francis Miller, David M....