资源分类
》 资源 》论文》Controlling Growing Tasks with Heterogeneous Agents

Controlling Growing Tasks with Heterogeneous Agents

2019-11-22 | |  45 |   37 |   0
Abstract We propose solutions for assignment of physical tasks to heterogeneous agents when the costs of the tasks change over time. We assume tasks have a natural growth rate which is counteracted by the work applied by the agents. As the future cost of a task depends on the agents allocation, reasoning must be both spatial and temporal to effectively minimize the growth so tasks can be completed. We present optimal solutions for two general classes of growth functions and heuristic solutions for other cases. Empirical results are given in RoboCup Rescue for agents with different capabilities.

上一篇：Distributed Breakout: Beyond Satisfaction

下一篇：Using Message-Passing DCOP Algorithms to Solve Energy-Efficient Smart Environment Configuration Problems

用户评价
全部评价

热门资源

  • Learning to Predi...

    Much of model-based reinforcement learning invo...

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • The Variational S...

    Unlike traditional images which do not offer in...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...

  • Rating-Boosted La...

    The performance of a recommendation system reli...