Cognitive architectures aspire for generality both in terms of problem solving and learning across a range of problems, yet to date few examples of domain independent learning has...
Factored planning methods aim to exploit locality to efficiently solve large but "loosely coupled" planning problems by computing solutions locally and propagating limit...
Eric Fabre, Loig Jezequel, Patrik Haslum, Sylvie T...
Neural networks and other sophisticated machine learning algorithms frequently miss simple solutions that can be discovered by a more constrained learning methods. Transition from ...
As knowledge becomes the primary focus of work in many industries, virtual communities and groups are emerging as part of new organizational forms. Within these virtual forms, eff...
In this paper, we present a new hypergraph partitioning algorithm that jointly optimizes the number of hyperedge cuts and the number of shared vertices in nonlinear constrained op...