Titlebook: Autonomous Agents and Multiagent Systems; AAMAS 2016 Workshops Nardine Osman,Carles Sierra Conference proceedings 2016 Springer Internation

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Evaluating the Efficiency of Robust Team Formation Algorithms,ll problem sizes and prove that it is a .-factor approximation of the optimal solution, where . is the number of tasks to be completed. We also present three heuristic algorithms and an evolutionary computation approach which scales up?to larger problems. Another advantage of the evolutionary scheme

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Dynamics of Fairness in Groups of Autonomous Learning Agents,ehavior into different strategies, depending on factors such as the minimum number of accepting Responders (to achieve group acceptance) or the group size. Overall, our simulations show that stringent group criteria leverage fairer proposals. We find these conclusions robust to (.) asynchronous and

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Joe Lorkowski,Vladik Kreinovich, with different tradeoffs between responsiveness and computational overhead. We also discuss opportunities and challenges in extending our proposed semantics to richer forms of uncertainty, and to other agent architectures besides the decision-theoretic agents that have been our initial focus of st

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Intelligent Systems Reference Libraryll problem sizes and prove that it is a .-factor approximation of the optimal solution, where . is the number of tasks to be completed. We also present three heuristic algorithms and an evolutionary computation approach which scales up?to larger problems. Another advantage of the evolutionary scheme