Internet facilitates easy access to data, information, and knowledge sources available online. This provides an unprecedented opportunity to empower decision support systems with ...
Our focus is on designing adaptable agents for highly dynamic environments. Wehave implementeda reinforcement learning architecture as the reactive componentof a twolayer control ...
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...