Machine learning systems offer unparalled flexibility in dealing with evolving input in a variety of applications, such as intrusion detection systems and spam e-mail filtering. H...
Marco Barreno, Blaine Nelson, Russell Sears, Antho...
Recent advances in technology allow multi-agent systems to be deployed in cooperation with or as a service for humans. Typically, those systems are designed assuming individually ...
Reward shaping is a well-known technique applied to help reinforcement-learning agents converge more quickly to nearoptimal behavior. In this paper, we introduce social reward sha...
Monica Babes, Enrique Munoz de Cote, Michael L. Li...
Intentions have been widely studied in AI, both in the context of decision-making within individual agents and in multiagent systems. Work on intentions in multi-agent systems has...
The static asset protection problem (SAP) in a road network is that of allocating resources to protect vertices, given any possible behavior by an adversary determined to attack t...
John P. Dickerson, Gerardo I. Simari, V. S. Subrah...