In this paper we report on using a relational state space in multi-agent reinforcement learning. There is growing evidence in the Reinforcement Learning research community that a r...
Tom Croonenborghs, Karl Tuyls, Jan Ramon, Maurice ...
The goal of the paper is to create a model for investigating the character of relationships between the freedom and restrictions in the terrorism context, in order to find out how ...
We present an interactive learning method that enables a user to iteratively refine a regression model. The user examines the output of the model, visualized as the vertical axis ...
The ability to coordinate effectively is critical for agents to accomplish their goals in a multi-agent system. A number of researchers have modeled the coordination problem for m...
This paper presents a multi-agent model to support decisionmaking in organizations. The model is characterized by being interactive, distributed, and incremental and by the use of...