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Coordination and Multi-Tasking Using EMT

Coordination and Multi-Tasking Using EMT
Coordination and Multi-Tasking Using EMT
We introduce a multi-model variant of the EMT-based control algorithm. The new algorithm, MM-EMT, is capable of balancing several control tasks expressed using separate dynamic models with a common action space. Such multiple models are common in both single-agent environments, when the agent has multiple tasks to achieve, and in team activities, when agent actions affect both the local agent’s task as well as the overall team’s coordination. To demonstrate the behaviour that MM-EMT engenders, several experimental setups were devised. Simulation results support the effectiveness of the approach, which in the multiagent scenario is expressed in theMM-EMT algorithm’s ability to balance local and team-coordinated motion requirements.
Rabinovich, Zinovi
573422bf-523d-466b-a047-7a92917102e7
Pochter, Nir
18b6b6d7-e30e-4127-bd64-5dcc98db1173
Rosenschein, Jeffrey S.
829d6714-6345-40c5-8bf9-01496be375de
Rabinovich, Zinovi
573422bf-523d-466b-a047-7a92917102e7
Pochter, Nir
18b6b6d7-e30e-4127-bd64-5dcc98db1173
Rosenschein, Jeffrey S.
829d6714-6345-40c5-8bf9-01496be375de

Rabinovich, Zinovi, Pochter, Nir and Rosenschein, Jeffrey S. (2008) Coordination and Multi-Tasking Using EMT. The Twenty-Third National Conference on Artificial Intelligence (AAAI 2008), Chicago, Illinois,. 13 - 17 Jul 2008. (Submitted)

Record type: Conference or Workshop Item (Paper)

Abstract

We introduce a multi-model variant of the EMT-based control algorithm. The new algorithm, MM-EMT, is capable of balancing several control tasks expressed using separate dynamic models with a common action space. Such multiple models are common in both single-agent environments, when the agent has multiple tasks to achieve, and in team activities, when agent actions affect both the local agent’s task as well as the overall team’s coordination. To demonstrate the behaviour that MM-EMT engenders, several experimental setups were devised. Simulation results support the effectiveness of the approach, which in the multiagent scenario is expressed in theMM-EMT algorithm’s ability to balance local and team-coordinated motion requirements.

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More information

Submitted date: 2008
Additional Information: Event Dates: July 13-17
Venue - Dates: The Twenty-Third National Conference on Artificial Intelligence (AAAI 2008), Chicago, Illinois,, 2008-07-13 - 2008-07-17
Organisations: Electronics & Computer Science

Identifiers

Local EPrints ID: 265767
URI: http://eprints.soton.ac.uk/id/eprint/265767
PURE UUID: 37f68cec-b5f6-4b83-b2f9-86577164809d

Catalogue record

Date deposited: 20 May 2008 11:17
Last modified: 14 Mar 2024 08:14

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Contributors

Author: Zinovi Rabinovich
Author: Nir Pochter
Author: Jeffrey S. Rosenschein

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