This paper investigates cooperative search strategies for agents engaged in costly search in a complex environment. Searching cooperatively, several search goals can be satisfied w...
This paper examines a method of clustering within a fully decentralized multi-agent system. Our goal is to group agents with similar objectives or data, as is done in traditional ...
Elth Ogston, Benno J. Overeinder, Maarten van Stee...
Negotiation techniques have been demonstrated to be effective in solving complex multi-objective problems. When the optimization process operates on continuous variables, it can b...
We present our work on using statistical, corpus-based machine learning techniques to simultaneously recognize an agent's current goal schemas at various levels of a hierarch...
This paper introduces an approach to automatic basis function construction for Hierarchical Reinforcement Learning (HRL) tasks. We describe some considerations that arise when con...