The functional characteristics of market-based solutions are typically best observed through the medium of simulation, data-gathering and subsequent visualization. We previously d...
Peter Gradwell, Michel A. Oey, Reinier J. Timmer, ...
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are evolving as a popular approach for modeling multiagent systems, and many different algorithms ha...
The central problem of designing intelligent robot systems which learn by demonstrations of desired behaviour has been largely studied within the field of robotics. Numerous archi...
Learning to converge to an efficient, i.e., Pareto-optimal Nash equilibrium of the repeated game is an open problem in multiagent learning. Our goal is to facilitate the learning ...
This paper reports on a novel decentralised technique for planning agent schedules in dynamic task allocation problems. Specifically, we use a Markov game formulation of these pr...
Archie C. Chapman, Rosa Anna Micillo, Ramachandra ...