Cooperation and learning are two ways in which an agent can improve its performance. Cooperative Multiagent Learning is a framework to analyze the tradeoff between cooperation and ...
This paper describes results from a series of experimental studies to explore issues related to structuring productive group dynamics for collaborative learning using an adaptive ...
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
We report on the performance of an enhanced version of the “Davis-Putnam” (DP) proof procedure for propositional satisfiability (SAT) on large instances derived from realworld...
Empirical work with "Belvedere," a software environment for the construction of diagrammatic representations of evidential relations, is summarized, leading to the hypot...