Motivated by a machine learning perspective—that gametheoretic equilibria constraints should serve as guidelines for predicting agents’ strategies, we introduce maximum causal...
We develop an algorithm for opponent modeling in large extensive-form games of imperfect information. It works by observing the opponent’s action frequencies and building an opp...
Autonomy requires robustness. The use of unmanned (autonomous) vehicles is appealing for tasks which are dangerous or dull. However, increased reliance on autonomous robots increa...
Eliahu Khalastchi, Gal A. Kaminka, Meir Kalech, Ra...
The primary objective of this paper is to introduce Fuzzy Rule-Based Systems (FRBSs) as a relatively new technology into airport transportation research, with a special emphasis o...
Jun Chen, Stefan Ravizza, Jason A. D. Atkin, Paul ...
Abstract—In this paper, we propose a framework for employing opposition-based learning to assist evolutionary algorithms in solving discrete and combinatorial optimization proble...