Abstract. This work presents a multiagent framework design for DemandResponsive Transportation, considering a virtual enterprise domain. The agent architecture obtained provides a ...
We are developing Companion Cognitive Systems, a new kind of software that can be effectively treated as a collaborator. Aside from their potential utility, we believe this effort...
We present several new algorithms for multiagent reinforcement learning. A common feature of these algorithms is a parameterized, structured representation of a policy or value fu...
Carlos Guestrin, Michail G. Lagoudakis, Ronald Par...
We introduce an adversarial planning algorithm based on game tree search, which is applicable in large-scale multiplayer domains. In order to tackle the scalability issues of game...
Abstract. Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. There exist several convergent and consistent RL algorithms which have been intensivel...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...