In this paper, we show how adaptive prototype optimization can be used to improve the performance of function approximation based on Kanerva Coding when solving largescale instanc...
In this paper, we investigate multi-agent learning (MAL) in a multi-agent resource selection problem (MARS) in which a large group of agents are competing for common resources. Si...
In this paper, we investigate Reinforcement learning (RL) in multi-agent systems (MAS) from an evolutionary dynamical perspective. Typical for a MAS is that the environment is not ...
Karl Tuyls, Pieter Jan't Hoen, Bram Vanschoenwinke...
In concurrent cooperative multiagent learning, each agent simultaneously learns to improve the overall performance of the team, with no direct control over the actions chosen by i...
In many Multi-Agent Systems (MAS), agents (even if selfinterested) need to cooperate in order to maximize their own utilities. Most of the multi-agent learning algorithms focus on...
Jose Enrique Munoz de Cote, Alessandro Lazaric, Ma...