On the response of EMT-based control to interacting targets and models

Zinovi Rabinoyich; Jeffrey S. Rosenschein

doi:10.1145/1160633.1160718

On the response of EMT-based control to interacting targets and models

Zinovi Rabinoyich^*, Jeffrey S. Rosenschein

^*Corresponding author for this work

The Rachel and Selim Benin School of Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

A novel control mechanism was recently introduced based on Extended Markov Tracking (EMT) [9, 10]. In this paper, we present a study of its response to multiple interacting control goals. We show a simple extension that can be integrated into EMT-based control, and which provides it with the ability to handle several behavioral targets. Experimental support for the validity of this extension is provided. We also describe an experiment with a simulated robot, where EMT-based controllers interact and interfere indirectly via the environment. Experiments support the resilience of multiagent EMT-based team control to potential conflicts that may appear within a team.

Original language	English
Title of host publication	Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems
Pages	465-470
Number of pages	6
DOIs	https://doi.org/10.1145/1160633.1160718
State	Published - 2006
Event	Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS - Hakodate, Japan Duration: 8 May 2006 → 12 May 2006

Publication series

Name	Proceedings of the International Conference on Autonomous Agents
Volume	2006

Conference

Conference	Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Country/Territory	Japan
City	Hakodate
Period	8/05/06 → 12/05/06

Keywords

Autonomous robots and robot teams
Control
Extended Markov tracking
Markovian environment

Access to Document

10.1145/1160633.1160718

Cite this

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title = "On the response of EMT-based control to interacting targets and models",

abstract = "A novel control mechanism was recently introduced based on Extended Markov Tracking (EMT) [9, 10]. In this paper, we present a study of its response to multiple interacting control goals. We show a simple extension that can be integrated into EMT-based control, and which provides it with the ability to handle several behavioral targets. Experimental support for the validity of this extension is provided. We also describe an experiment with a simulated robot, where EMT-based controllers interact and interfere indirectly via the environment. Experiments support the resilience of multiagent EMT-based team control to potential conflicts that may appear within a team.",

keywords = "Autonomous robots and robot teams, Control, Extended Markov tracking, Markovian environment",

author = "Zinovi Rabinoyich and Rosenschein, {Jeffrey S.}",

year = "2006",

doi = "10.1145/1160633.1160718",

language = "אנגלית",

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note = "Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS ; Conference date: 08-05-2006 Through 12-05-2006",

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Rabinoyich, Z & Rosenschein, JS 2006, On the response of EMT-based control to interacting targets and models. in Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems. Proceedings of the International Conference on Autonomous Agents, vol. 2006, pp. 465-470, Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, Hakodate, Japan, 8/05/06. https://doi.org/10.1145/1160633.1160718

On the response of EMT-based control to interacting targets and models. / Rabinoyich, Zinovi; Rosenschein, Jeffrey S.
Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems. 2006. p. 465-470 (Proceedings of the International Conference on Autonomous Agents; Vol. 2006).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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On the response of EMT-based control to interacting targets and models

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Keywords

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