Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Games may be represented in many different ways, and different representations of games affect the complexity of problems associated with games, such as finding a Nash equilib...
In contrast to classical game theoretic analysis of simultaneous and sequential play in bimatrix games, Steven Brams has proposed an alternative framework called the Theory of Mov...
Scalable coordination is a key challenge in deployment of multiagent systems. Resource usage is one part of agent behavior which naturally lends itself to abstraction. CyberOrgs i...
This paper reports experiences and outcomes of designing and developing an agent–based, autonomous mission control system for an unmanned aerial vehicle (UAV). Most UAVs are not...