This study proposes a simple computational model of evolutionary learning in organizations informed by genetic algorithms. Agents who interact only with neighboring partners seek ...
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
In this paper, we describe an evolutionary approach to one of the most challenging problems in computer music: modeling the knowledge applied by a musician when performing a score...
Rafael Ramirez, Amaury Hazan, Jordi Marine, Esteba...
In this paper we propose a computational model for human-agent and agent-agent conversation. This model has two fundamental characteristics: (1) it takes into account the implicit ...
We investigate and discuss safety and privacy preserving properties of a game-theortic based coalition algorithm KCA for forming kernel stable coalitions among information agents ...