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A polynomial time optimal algorithm for robot-human search under uncertainty

A polynomial time optimal algorithm for robot-human search under uncertainty
A polynomial time optimal algorithm for robot-human search under uncertainty
This paper studies a search problem involving a robot that is searching for a certain item in an uncertain environment (e.g., searching minerals on Moon) that allows only limited interaction with humans. The uncertainty of the environment comes from the rewards of undiscovered items and the availability of costly human help. The goal of the robot is to maximize the reward of the items found while minimising the search costs. We show that this search problem is polynomially solvable with a novel integration of the human help, which has not been studied in the literature before. Furthermore, we empirically evaluate our solution with simulations and show that it significantly outperforms several benchmark approaches.
Chen, Shaofei
7b9a7423-a4d1-46a5-9188-b5342435d362
Baarslag, Tim
a7c541d8-8141-467b-a08c-7a81cd69920e
Zhao, Dengji
731b17f8-df94-49cb-b45d-8edf05c59edf
Chen, Jing
5d1f11be-b12a-4517-9035-1b8b16078087
Shen, Lincheng
971267ff-c9ac-43d4-8526-6590c9e7b9ee
Chen, Shaofei
7b9a7423-a4d1-46a5-9188-b5342435d362
Baarslag, Tim
a7c541d8-8141-467b-a08c-7a81cd69920e
Zhao, Dengji
731b17f8-df94-49cb-b45d-8edf05c59edf
Chen, Jing
5d1f11be-b12a-4517-9035-1b8b16078087
Shen, Lincheng
971267ff-c9ac-43d4-8526-6590c9e7b9ee

Chen, Shaofei, Baarslag, Tim, Zhao, Dengji, Chen, Jing and Shen, Lincheng (2016) A polynomial time optimal algorithm for robot-human search under uncertainty. The 25th International Joint Conference on Artificial Intelligence, Argentina. 25 - 31 Jul 2016. 7 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

This paper studies a search problem involving a robot that is searching for a certain item in an uncertain environment (e.g., searching minerals on Moon) that allows only limited interaction with humans. The uncertainty of the environment comes from the rewards of undiscovered items and the availability of costly human help. The goal of the robot is to maximize the reward of the items found while minimising the search costs. We show that this search problem is polynomially solvable with a novel integration of the human help, which has not been studied in the literature before. Furthermore, we empirically evaluate our solution with simulations and show that it significantly outperforms several benchmark approaches.

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More information

Published date: July 2016
Venue - Dates: The 25th International Joint Conference on Artificial Intelligence, Argentina, 2016-07-25 - 2016-07-31
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 396231
URI: https://eprints.soton.ac.uk/id/eprint/396231
PURE UUID: ee36845a-acb6-4ba6-8168-09ddf52eedf2
ORCID for Tim Baarslag: ORCID iD orcid.org/0000-0002-1662-3910

Catalogue record

Date deposited: 01 Jun 2016 11:28
Last modified: 06 Jun 2018 12:22

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