Casting planning problems as propositional satis ability problems has recently been shown to be an effective way of scaling up plan synthesis. Until now, the bene ts of this appro...
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...
In this paper, we propose a genetic network programming (GNP) architecture using a coevolution model called automatically defined groups (ADG). The GNP evolves networks for describ...
The effectiveness of simulation-based training for individual tasks – such as piloting skills – is well established, but its use for team training raises challenging technical...
David R. Traum, Jeff Rickel, Jonathan Gratch, Stac...
We survey some issues that relate to context dependence and context sensitivity in the development of software, particularly in relation to information systems by defining a range...