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...
Agent description and discovery (ADD) is a critical infrastructure for open multi-agent services. As multi-agent systems grow larger and more diverse, it becomes harder to locate ...
This paper proposed a new approach that integrated an artificial market simulation and text-mining with real information. In this approach, economic trends were extracted from te...
In this paper, we present a multi-agent system implementing a fully distributed Social Network System supporting user profiles as FOAF profiles. This system is built around the ide...
Holonic Multi-Agent Systems (HMAS) are a convenient way to engineer complex and open systems. In such systems, agents have to be able to self-organize to satisfy their goals. Our w...
Sebastian Rodriguez, Nicolas Gaud, Vincent Hilaire...