TítuloImproving individual learning capabilities in Multi-Agent Systems
Publication TypeConference Paper
Year of Publication2006
AuthorsArmengol E, Puertas E
Conference NameWorkshop on Adaptation and Learning in autonomous agents and multi-agent systems. AAMAS-2006
Resumen

In multi-agent systems, individual learning capabilities can be improved thanks to the interaction with other agents. In the classification problem solving task each agent is able to solve the problems alone, but in a collaborative scenario, an agent can take advantage of the knowledge of others. In our approach, when an agent decides to collaborate with other agents, it reaches the solution taking into account the justifications that other agents have given about the solution they propose. Moreover, the agent learns to solve new problems using the justifications from other agents and checking their answers, as well as to solve further problems on its own.