Heuristics on the Data-Collecting Robot Problem with Immediate Rewards

• Published in: PRIMA 2016: Principles and Practice of Multi-Agent Systems pp. 131 - 148
• Main Authors: Xing, Zhi, Oh, Jae C.
• Format: Book Chapter
• Language: English
• Published: Cham Springer International Publishing 2016
• Series: Lecture Notes in Computer Science
• Subjects: Adversary route planning; Autonomous systems; Multi-robot systems
• ISBN: 3319448315; 9783319448312
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-44832-9_8

We propose the Data-collecting Robot Problem, where robots collect data as they visit nodes in a graph, and algorithms to solve it. There are two variations of the problem: the delayed-reward problem, in which robots must travel back to the base station to deliver the data collected and to receive rewards; and the immediate-reward problem, in which the reward is immediately given to the robots as they visit each node. The delayed-reward problem is discussed in one of the authors’ work. This paper focuses on the immediate-reward problem. The solution structure has a clustering step and a tour-building step. We propose Progressive Gain-aware Clustering that finds good quality solutions with efficient time complexity. Among the six proposed tour-building heuristics, Greedy Insertion and Total-Loss algorithms perform best when data rewards are different.