In large multiagent games, partial observability, coordination, and credit assignment persistently plague attempts to design good learning algorithms. We provide a simple and efï¬...
We study how to learn to play a Pareto-optimal strict Nash equilibrium when there exist multiple equilibria and agents may have different preferences among the equilibria. We focu...
This paper reports on the implementation and realization of software agents as teaching assistants in the distance learning environment. The software agent we built is able to ext...
This paper presents the key features of a new negotiation model for autonomous agents. The model is generic, handles multi-party and multi-issue negotiation, acknowledges the role...
Fernando Lopes, Augusto Q. Novais, Nuno J. Mamede,...
In this paper, we propose a new integration approach to simulate an Autonomous Virtual Agent's cognitive learning of a task for interactive Virtual Environment applications. O...