—Finding the most interesting correlations among items is essential for problems in many commercial, medical, and scientific domains. Much previous research focuses on finding ...
Previous work in multiagent coordination has addressed the challenge of planning in domains where agents must optimize a global goal, while satisfying local resource constraints. ...
Emma Bowring, Zhengyu Yin, Rob Zinkov, Milind Tamb...
This paper describes the design, implementation, visualizations, results and lessons learned of a novel real-world socio-technical research system for the purpose of rescheduling ...
Erwin J. W. Abbink, David G. A. Mobach, Pieter-Jan...
Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...
Commitment-modeled protocols enable flexible and robust interactions among agents. However, existing work has focused on features and capabilities of protocols without considerin...