Agent-based simulations are an increasingly popular means of exploring and understanding complex social systems. In order to be useful, these simulations must capture a range of a...
David Scerri, Alexis Drogoul, Sarah L. Hickmott, L...
This paper introduces an approach to automatic basis function construction for Hierarchical Reinforcement Learning (HRL) tasks. We describe some considerations that arise when con...
This paper proposes a framework for agent-based distributed machine learning and data mining based on (i) the exchange of meta-level descriptions of individual learning processes ...
Cooperative negotiation is proved to be an effective paradigm to solve complex dynamic multi-objective problems in which each objective is associated to an agent. When the multi-o...
POMDPs are a popular framework for representing decision making problems that contain uncertainty. The high computational complexity of finding exact solutions to POMDPs has spaw...