A major challenge for traditional approaches to multiagent learning is to train teams that easily scale to include additional agents. The problem is that such approaches typically...
David B. D'Ambrosio, Joel Lehman, Sebastian Risi, ...
This paper analyzes bilateral multi-issue negotiation between selfinterested agents. Specifically, we consider the case where issues are divisible, there are time constraints in ...
S. Shaheen Fatima, Michael Wooldridge, Nicholas R....
This paper presents a theoretical study of decentralized control for sensing-based shape formation on modular multirobot systems, where the desired shape is specified in terms of ...
Agent-based simulations are an increasingly popular means of exploring and understanding complex social systems. In order to be useful, these simulations must capture a range of a...
David Scerri, Alexis Drogoul, Sarah L. Hickmott, L...
Cooperative multiagent probabilistic inference can be applied in areas such as building surveillance and complex system diagnosis to reason about the states of the distributed unc...