故障や敵対的環境に強いマルチエージェントタスク割り当て
Robust Multi-Agent Task Assignment in Failure-Prone and Adversarial Environments
エージェントの故障を考慮しつつシステム全体の性能を最大化するタスク割り当て問題を定式化し、確率的・敵対的故障の両方に対して最適または準最適解を与える効率的アルゴリズムを提案した。
著者: Russell Schwartz, Pratap Tokekar
分類: cs.RO, cs.MA
原文アブストラクト
The problem of assigning agents to tasks is a central computational challenge in many multi-agent autonomous systems. However, in the real world, agents are not always perfect and may fail due to a number of reasons. A motivating application is where the agents are robots that operate in the physical world and are susceptible to failures. This paper studies the problem of Robust Multi-Agent Task Assignment, which seeks to find an assignment that maximizes overall system performance while accounting for potential failures of the agents. We investigate both, stochastic and adversarial failures under this framework. For both cases, we present efficient algorithms that yield optimal or near-optimal results.
