Intelligent agents that are intended to work in dynamic environments must be able to gracefully handle unsuccessful tasks and plans. In addition, such agents should be able to mak...
John Thangarajah, James Harland, David N. Morley, ...
We present a framework that enables a belief-desire-intention (BDI) agent to dynamically choose its intention reconsideration policy in order to perform optimally in accordance wi...
Planning under uncertainty is an important and challenging problem in multiagent systems. Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful fr...
Existing modeling frameworks for manufacturing system control can be classified into hierarchical, heterarchical, and hybrid control frameworks. The main drawbacks of existing fram...
Sunderesh S. Heragu, Robert J. Graves, Byung-In Ki...
This paper addresses the problem of constructing good action selection policies for agents acting in partially observable environments, a class of problems generally known as Part...