Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Distributed Constraint Optimization (DCOP) is a general framework that can model complex problems in multi-agent systems. Several current algorithms that solve general DCOP instan...
The aggregation of conflicting preferences is a key issue in multiagent systems. Due to its universality, voting has a central role among preference aggregation mechanisms. Votin...
This paper describes an integrated system for coordinating multiple rover behavior with the overall goal of collecting planetary surface data. The MISUS system combines techniques...
Tara A. Estlin, Daniel M. Gaines, Forest Fisher, R...
The rapid changing business environment of high-tech asset intensive enterprises such as semiconductor manufacturing constantly drives production managers to look for better solut...
Malcolm Yoke-Hean Low, Kong Wei Lye, Peter Lenderm...