Multi-agent systems are prone to failures typical of any distributed system. Agents and resources may become unavailable due to machine crashes, communication breakdowns, process ...
Most work on intelligent information agents has thus far focused on systems that are accessible through the World Wide Web. As demanding schedules prohibit people from continuous ...
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
Physical domains are notoriously hard to model completely and correctly, especially to capture the dynamics of the environment. Moreover, since environments change, it is even mor...
Abstract. As the popularity of social networks expands, the information users expose to the public has potentially dangerous implications for individual privacy. While social netwo...