Game tree search for minimizing detectability and maximizing visibility
Name
10514_2020_9963_ReferencePDF.pdf
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2.85 MB
Format
Adobe PDF
Checksum (MD5)
d3fcd9b45cbbbbb3f08d81acd137beeb
Author(s)
Zhang, Zhongshun
Smereka, Jonathon M.
Lee, Joseph
Zhou, Lifeng
Sung, Yoonchang
Tokekar, Pratap
Date Issued
January 20, 2021
Publisher
Springer US
Version
Author's final manuscript
Abstract
Abstract
We introduce and study the problem of planning a trajectory for an agent to carry out a scouting mission while avoiding being detected by an adversarial opponent. This introduces a multi-objective version of classical visibility-based target search and pursuit-evasion problem. In our formulation, the agent receives a positive reward for increasing its visibility (by exploring new regions) and a negative penalty every time it is detected by the opponent. The objective is to find a finite-horizon path for the agent that balances the trade off between maximizing visibility and minimizing detectability. We model this problem as a discrete, sequential, two-player, zero-sum game. We use two types of game tree search algorithms to solve this problem: minimax search tree and Monte-Carlo search tree. Both search trees can yield the optimal policy but may require possibly exponential computational time and space. We first propose three pruning techniques to reduce the computational time while preserving optimality guarantees. When the agent and the opponent are located far from each other initially, we present a variable resolution technique with longer planning horizon to further reduce computational time. Simulation results show the effectiveness of the proposed strategies in terms of computational time.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1007/s10514-020-09963-4
