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Decentralised Coordination in RoboCup Rescue

Decentralised Coordination in RoboCup Rescue
Decentralised Coordination in RoboCup Rescue
Emergency responders are faced with a number of significant challenges when managing major disasters. First, the number of rescue tasks posed is usually larger than the number of responders (or agents) and the resources available to them. Second, each task is likely to require a different level of effort in order to be completed by its deadline. Third, new tasks may continually appear or disappear from the environment, thus requiring the responders to quickly recompute their allocation of resources. Fourth, forming teams or coalitions of multiple agents from different agencies is vital since no single agency will have all the resources needed to save victims, unblock roads, and extinguish the ?res which might erupt in the disaster space. Given this, coalitions have to be efficiently selected and scheduled to work across the disaster space so as to maximise the number of lives and the portion of the infrastructure saved. In particular, it is important that the selection of such coalitions should be performed in a decentralised fashion in order to avoid a single point of failure in the system. Moreover, it is critical that responders communicate only locally given they are likely to have limited battery power or minimal access to long range communication devices. Against this background, we provide a novel decentralised solution to the coalition formation process that pervades disaster management. More specifically, we model the emergency management scenario defined in the RoboCup Rescue disaster simulation platform as a Coalition Formation with Spatial and Temporal constraints (CFST) problem where agents form coalitions in order to complete tasks, each with different demands. In order to design a decentralised algorithm for CFST we formulate it as a Distributed Constraint Optimisation problem and show how to solve it using the state-of-the-art Max-Sum algorithm that provides a completely decentralised message-passing solution. We then provide a novel algorithm (F-Max-Sum) that avoids sending redundant messages and efficiently adapts to changes in the environment. In empirical evaluations, our algorithm is shown to generate better solutions than other decentralised algorithms used for this problem.
1-15
Ramchurn, Sarvapali
1d62ae2a-a498-444e-912d-a6082d3aaea3
Farinelli, Alessandro
d2f26070-f403-4cae-b712-7097cb2e3fc6
Macarthur, Kathryn
4c7db797-1679-4fd1-9dac-26f84bd5debd
Polukarov, Mariya
bd2f0623-9e8a-465f-8b29-851387a64740
Jennings, Nick
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Ramchurn, Sarvapali
1d62ae2a-a498-444e-912d-a6082d3aaea3
Farinelli, Alessandro
d2f26070-f403-4cae-b712-7097cb2e3fc6
Macarthur, Kathryn
4c7db797-1679-4fd1-9dac-26f84bd5debd
Polukarov, Mariya
bd2f0623-9e8a-465f-8b29-851387a64740
Jennings, Nick
ab3d94cc-247c-4545-9d1e-65873d6cdb30

Ramchurn, Sarvapali, Farinelli, Alessandro, Macarthur, Kathryn, Polukarov, Mariya and Jennings, Nick (2010) Decentralised Coordination in RoboCup Rescue. The Computer Journal, 53 (9), 1-15.

Record type: Article

Abstract

Emergency responders are faced with a number of significant challenges when managing major disasters. First, the number of rescue tasks posed is usually larger than the number of responders (or agents) and the resources available to them. Second, each task is likely to require a different level of effort in order to be completed by its deadline. Third, new tasks may continually appear or disappear from the environment, thus requiring the responders to quickly recompute their allocation of resources. Fourth, forming teams or coalitions of multiple agents from different agencies is vital since no single agency will have all the resources needed to save victims, unblock roads, and extinguish the ?res which might erupt in the disaster space. Given this, coalitions have to be efficiently selected and scheduled to work across the disaster space so as to maximise the number of lives and the portion of the infrastructure saved. In particular, it is important that the selection of such coalitions should be performed in a decentralised fashion in order to avoid a single point of failure in the system. Moreover, it is critical that responders communicate only locally given they are likely to have limited battery power or minimal access to long range communication devices. Against this background, we provide a novel decentralised solution to the coalition formation process that pervades disaster management. More specifically, we model the emergency management scenario defined in the RoboCup Rescue disaster simulation platform as a Coalition Formation with Spatial and Temporal constraints (CFST) problem where agents form coalitions in order to complete tasks, each with different demands. In order to design a decentralised algorithm for CFST we formulate it as a Distributed Constraint Optimisation problem and show how to solve it using the state-of-the-art Max-Sum algorithm that provides a completely decentralised message-passing solution. We then provide a novel algorithm (F-Max-Sum) that avoids sending redundant messages and efficiently adapts to changes in the environment. In empirical evaluations, our algorithm is shown to generate better solutions than other decentralised algorithms used for this problem.

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More information

Submitted date: 1 March 2010
Published date: 2010
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 268499
URI: http://eprints.soton.ac.uk/id/eprint/268499
PURE UUID: a3da9063-1021-4684-b49b-0c368b384626
ORCID for Sarvapali Ramchurn: ORCID iD orcid.org/0000-0001-9686-4302

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Date deposited: 11 Feb 2010 16:02
Last modified: 15 Mar 2024 03:22

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Contributors

Author: Sarvapali Ramchurn ORCID iD
Author: Alessandro Farinelli
Author: Kathryn Macarthur
Author: Mariya Polukarov
Author: Nick Jennings

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