Different qualitative models have been proposed for decision under uncertainty in Artificial Intelli gence, but they generally fail to satisfy the princi ple of strict Pareto ...
Predictive accuracy has been used as the main and often only evaluation criterion for the predictive performance of classification learning algorithms. In recent years, the area ...
Efficient implementations of DPLL with the addition of clause learning are the fastest complete satisfiability solvers and can handle many significant real-world problems, such as...
In this paper, we define a simple but scalable framework for peer-to-peer data sharing systems, in which the problem of answering queries over a network of semantically related p...
Traditional single-agent search algorithms usually make simplifying assumptions (single search agent, stationary target, complete knowledge of the state, and sufficient time). The...
Mark Goldenberg, Alexander Kovarsky, Xiaomeng Wu, ...