论文标题
具有有限的计算和通信功能的常规机器人网络上的战略性多任务协调
Strategic multi-task coordination over regular networks of robots with limited computation and communication capabilities
论文作者
论文摘要
协调是多代理系统中的理想功能，允许执行单个代理无法执行的任务。我们研究了一个选择执行多个任务之一的战略代理团队的协调。我们采用一个随机框架，在该框架中，代理在两个不同的任务之间决定了它们的难度是随机分布并部分观察到的。我们表明，在任务困难上存在弥漫性先验分布，存在具有简单直观的线性结构的NASH平衡。此外，我们表明，当先前的分布没有分散时，任何代理对仿射策略概况的最佳响应都可能是非线性的。最后，我们指出了一种算法，该算法使我们能够在仿射策略类别中有效计算数据驱动的NASH平衡。
Coordination is a desirable feature in multi-agent systems, allowing the execution of tasks that would be impossible by individual agents. We study coordination by a team of strategic agents choosing to undertake one of the multiple tasks. We adopt a stochastic framework where the agents decide between two distinct tasks whose difficulty is randomly distributed and partially observed. We show that a Nash equilibrium with a simple and intuitive linear structure exists for diffuse prior distributions on the task difficulties. Additionally, we show that the best response of any agent to an affine strategy profile can be nonlinear when the prior distribution is not diffuse. Finally, we state an algorithm that allows us to efficiently compute a data-driven Nash equilibrium within the class of affine policies.
