Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in largescale systems. In this work, we develop an organization-b...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
Multiagent environments are often highly dynamic and only partially observable which makes deliberative action planning computationally hard. In many such environments, however, a...
Team decision making under stress involving multiple contexts is an extremely challenging issue faced by various real world application domains. This research is targeted at coupl...
Xiaocong Fan, Bingjun Sun, Shuang Sun, Michael D. ...
In this paper, a new agent development platform, which includes built-in features for semantic web based multi agent system development, is introduced. All agents and services in ...
In this paper we consider distributed K-Nearest Neighbor (KNN) search and range query processing in high dimensional data. Our approach is based on Locality Sensitive Hashing (LSH...