This paper presents an improved differential evolution (IDE) method for the solution of large-scale unit commitment (UC) problems. The objective of the proposed scheme is to determ...
We cast the word alignment problem as maximizing a submodular function under matroid constraints. Our framework is able to express complex interactions between alignment component...
Learning to converge to an efficient, i.e., Pareto-optimal Nash equilibrium of the repeated game is an open problem in multiagent learning. Our goal is to facilitate the learning ...
In multiagent systems, strategic settings are often analyzed under the assumption that the players choose their strategies simultaneously. However, this model is not always realis...
This paper develops a model for exceptions and an approach for incorporating them in commitment protocols among autonomous agents. Modeling and handling exceptions is critical for...