Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in large-scale systems. In this work, we develop a supervision fr...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
To test large scale socially embedded systems, this paper proposes a multiagent-based participatory design that consists of two steps; 1) participatory simulation, where scenario-...
Coordinating multiple agents that need to perform a sequence of actions to maximize a system level reward requires solving two distinct credit assignment problems. First, credit m...
This paper studies iterative learning control (ILC) in a multi-agent framework. A group of agents simultaneously and repeatedly perform the same task. The agents improve their perf...
In this paper we describe the Agent World Editor, a tool for designing multi-agent systems and generating executable agent code. The tool also unifies the handling of different a...