Distributed allocation and multiagent coordination problems can be solved through combinatorial auctions. However, most of the existing winner determination algorithms for combina...
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...
This paper reports experiences and outcomes of designing and developing an agent–based, autonomous mission control system for an unmanned aerial vehicle (UAV). Most UAVs are not...
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...
This paper develops a model for exceptions and an approach for incorporating them in commitment protocols among autonomous agents. Modeling and handling exceptions is critical for...