Article

TACOP: a cognitive agent for a naval training simulation environment

Authors:

Willem A. van Doesburg,

Annerieke Heuvelink,

Egon L. van den BroekAuthors Info & Claims

AAMAS '05: Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems

Pages 1363 - 1364

https://doi.org/10.1145/1082473.1082774

Published: 25 July 2005 Publication History

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Abstract

This paper describes how cognitive modeling can be exploited in the design of software agents that support naval training sessions. The architecture, specifications, and embedding of the cognitive agent in a simulation environment are described. Subsequently, the agent's functioning was evaluated in complex, real life training situations for naval officers.

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Oh SKim D(2021)Machine–Deep–Ensemble Learning Model for Classifying Cybersickness Caused by Virtual Reality ImmersionCyberpsychology, Behavior, and Social Networking10.1089/cyber.2020.0613Online publication date: 10-Aug-2021
https://doi.org/10.1089/cyber.2020.0613
Løvlid RAlstad AMevassvik Ode Reus NHenderson Hvan der Vecht BLuik THill RKuhl M(2013)Two approaches to developing a multi-agent system for battle command simulationProceedings of the 2013 Winter Simulation Conference: Simulation: Making Decisions in a Complex World10.5555/2675983.2676170(1491-1502)Online publication date: 8-Dec-2013
https://dl.acm.org/doi/10.5555/2675983.2676170
Lovlid RAlstad AMevassvik Ode Reus NHenderson Hvan der Vecht BLuik T(2013)Two approaches to developing a multi-agent system for battle command simulation2013 Winter Simulations Conference (WSC)10.1109/WSC.2013.6721533(1491-1502)Online publication date: Dec-2013
https://doi.org/10.1109/WSC.2013.6721533
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Index Terms

TACOP: a cognitive agent for a naval training simulation environment
1. Applied computing
  1. Computers in other domains
2. Computing methodologies
  1. Artificial intelligence
  2. Modeling and simulation

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Information

Published In

AAMAS '05: Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems

July 2005

1407 pages

ISBN:1595930930

DOI:10.1145/1082473

Program Chairs:
Michal Pechoucek
Czech Republic
,
Donald Steiner
USA
,
Simon Thompson
UK

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 July 2005

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Conference

AAMAS05

Sponsor:

SIGAI

AAMAS05: AAMAS '05 - Fourth International Joint Conference on Autonomous Agents and Multiagent Systems 2005

July 25 - 29, 2005

The Netherlands

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Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

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Cited By

View all

Oh SKim D(2021)Machine–Deep–Ensemble Learning Model for Classifying Cybersickness Caused by Virtual Reality ImmersionCyberpsychology, Behavior, and Social Networking10.1089/cyber.2020.0613Online publication date: 10-Aug-2021
https://doi.org/10.1089/cyber.2020.0613
Løvlid RAlstad AMevassvik Ode Reus NHenderson Hvan der Vecht BLuik THill RKuhl M(2013)Two approaches to developing a multi-agent system for battle command simulationProceedings of the 2013 Winter Simulation Conference: Simulation: Making Decisions in a Complex World10.5555/2675983.2676170(1491-1502)Online publication date: 8-Dec-2013
https://dl.acm.org/doi/10.5555/2675983.2676170
Lovlid RAlstad AMevassvik Ode Reus NHenderson Hvan der Vecht BLuik T(2013)Two approaches to developing a multi-agent system for battle command simulation2013 Winter Simulations Conference (WSC)10.1109/WSC.2013.6721533(1491-1502)Online publication date: Dec-2013
https://doi.org/10.1109/WSC.2013.6721533
Taranti PBreitman Kde Lucena CChoren RMcGraw RImsand EChinni M(2010)An approach to reduce the gap between conceptual and execution models in agent-directed simulationsProceedings of the 2010 Spring Simulation Multiconference10.1145/1878537.1878542(1-8)Online publication date: 11-Apr-2010
https://dl.acm.org/doi/10.1145/1878537.1878542
Reichel KHochgeschwender NVoos H(2008)OpCogProceedings of the 7th international joint conference on Autonomous agents and multiagent systems: industrial track10.5555/1402795.1402813(97-100)Online publication date: 12-May-2008
https://dl.acm.org/doi/10.5555/1402795.1402813
Sepulveda JRabelo LAkin HZhu YNicol DFujimoto R(2006)Modeling the effectiveness of underwater sonarProceedings of the 38th conference on Winter simulation10.5555/1218112.1218238(672-679)Online publication date: 3-Dec-2006
https://dl.acm.org/doi/10.5555/1218112.1218238
Schurr NPatil PPighin FTambe MNakashima HWellman MWeiss GStone P(2006)Using multiagent teams to improve the training of incident commandersProceedings of the fifth international joint conference on Autonomous agents and multiagent systems10.1145/1160633.1160924(1490-1497)Online publication date: 8-May-2006
https://dl.acm.org/doi/10.1145/1160633.1160924
Sepulveda JRabelo LAkin HZhu Y(2006)Modeling the Effectiveness of Underwater SonarProceedings of the 2006 Winter Simulation Conference10.1109/WSC.2006.323145(672-679)Online publication date: Dec-2006
https://doi.org/10.1109/WSC.2006.323145

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