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, ...
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...
Determining the provenance of data, i.e. the process that led to that data, is vital in many disciplines. For example, in science, the process that produced a given result must be...
Simon Miles, Steve Munroe, Michael Luck, Luc Morea...
Activity recognition is a key component for creating intelligent, multi-agent systems. Intrinsically, activity recognition is a temporal classification problem. In this paper, we...
Douglas L. Vail, Manuela M. Veloso, John D. Laffer...
We develop and implement a novel algorithm for discovering the optimal sets of premisses for proving and disproving conjectures in first-order logic. The algorithm uses interpret...