Abstract. Computational Game Theory is a way to study and evaluate behaviors using game theory models, via agent-based computer simulations. One of the most known example of this a...
This work presents a lookahead-based exploration strategy for a model-based learning agent that enables exploration of the opponent's behavior during interaction in a multi-a...
In this paper we address the problem of selfish behavior in ad hoc networks. We propose a strategy driven approach which aims at enforcing cooperation between network participant...
Marcin Seredynski, Pascal Bouvry, Mieczyslaw A. Kl...
Acknowledging the social functions that emotions serve, there has been growing interest in the interpersonal effect of emotion in human decision making. Following the paradigm of e...
Celso M. de Melo, Peter Carnevale, Jonathan Gratch
Reward shaping is a well-known technique applied to help reinforcement-learning agents converge more quickly to nearoptimal behavior. In this paper, we introduce social reward sha...
Monica Babes, Enrique Munoz de Cote, Michael L. Li...