Competitive Ant Coverage: The Value of Pursuit

Alon Shats, Michael Amir, Noa Agmon

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper studies the problem of Competitive Ant Coverage, in which two ant-like robots with very limited capabilities in terms of sensing range, computational power, and knowledge of the world compete in an area coverage task. We examine two variants of the problem that differ in the robot's objective: either being the First to Cover a Cell (FCC), or being the Last to Cover a Cell (LCC). Each robot's goal is to acquire (by visiting first or last, respectively) more cells than the opposing robot, and by that win the game. We examine the problem both theoretically and empirically, and show that the main strategy for dominance revolves around the ability to pursue: in LCC, we wish to pursue the opposing robot, whereas in FCC, we wish to create a scenario wherein the opposing robot pursues us. We find that this ability relies more heavily on knowledge of the opponent's strategy than on the robot's sensing capabilities. Moreover, given the robot's limited capabilities, we find that this knowledge-gap cannot be easily mitigated by learning.

Original languageEnglish
Title of host publication2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6733-6740
Number of pages8
ISBN (Electronic)9781665491907
DOIs
StatePublished - 2023
Event2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023 - Detroit, United States
Duration: 1 Oct 20235 Oct 2023

Publication series

NameIEEE International Conference on Intelligent Robots and Systems

Conference

Conference2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023
Country/TerritoryUnited States
CityDetroit
Period1/10/235/10/23

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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