Model docking using knowledge-level analysis

Ethan Trewhitt; Elizabeth Whitaker; Erica Briscoe; Lora Weiss

doi:10.1007/978-3-642-19656-0_17

Model docking using knowledge-level analysis

Ethan Trewhitt
, Elizabeth Whitaker
, Erica Briscoe
, Lora Weiss

Graduate Program in Acoustics

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

Abstract

This paper presents an initial approach for exploring the docking of social models at the knowledge level. We have prototyped a simple blackboard environment allowing for model docking experimentation. There are research challenges in identifying which models are appropriate to dock and the concepts that they should exchange to build a richer multi-scale view of the world. Our early approach includes docking of societal system dynamics models with individual and organizational behaviors represented in agent-based models. Case-based models allow exploration of historical knowledge by other models. Our research presents initial efforts to attain opportunistic, asynchronous interactions among multi-scale models through investigation and experimentation of knowledge-level model docking. A docked system can supply a multi-scale modeling capability to support a user's what-if analysis through combinations of case-based modeling, system dynamics approaches and agent-based models working together. An example is provided for the domain of terrorist recruiting.

Original language	English (US)
Title of host publication	Social Computing, Behavioral-Cultural Modeling and Prediction - 4th International Conference, SBP 2011, Proceedings
Pages	105-112
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-642-19656-0_17
State	Published - 2011
Event	4th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2011 - College Park, MD, United States Duration: Mar 29 2011 → Mar 31 2011

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6589 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	4th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2011
Country/Territory	United States
City	College Park, MD
Period	3/29/11 → 3/31/11

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 16 Peace, Justice and Strong Institutions

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-19656-0_17

Cite this

Trewhitt, E., Whitaker, E., Briscoe, E., & Weiss, L. (2011). Model docking using knowledge-level analysis. In Social Computing, Behavioral-Cultural Modeling and Prediction - 4th International Conference, SBP 2011, Proceedings (pp. 105-112). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6589 LNCS). https://doi.org/10.1007/978-3-642-19656-0_17

Trewhitt, Ethan ; Whitaker, Elizabeth ; Briscoe, Erica et al. / Model docking using knowledge-level analysis. Social Computing, Behavioral-Cultural Modeling and Prediction - 4th International Conference, SBP 2011, Proceedings. 2011. pp. 105-112 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Model docking using knowledge-level analysis",

abstract = "This paper presents an initial approach for exploring the docking of social models at the knowledge level. We have prototyped a simple blackboard environment allowing for model docking experimentation. There are research challenges in identifying which models are appropriate to dock and the concepts that they should exchange to build a richer multi-scale view of the world. Our early approach includes docking of societal system dynamics models with individual and organizational behaviors represented in agent-based models. Case-based models allow exploration of historical knowledge by other models. Our research presents initial efforts to attain opportunistic, asynchronous interactions among multi-scale models through investigation and experimentation of knowledge-level model docking. A docked system can supply a multi-scale modeling capability to support a user's what-if analysis through combinations of case-based modeling, system dynamics approaches and agent-based models working together. An example is provided for the domain of terrorist recruiting.",

author = "Ethan Trewhitt and Elizabeth Whitaker and Erica Briscoe and Lora Weiss",

year = "2011",

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booktitle = "Social Computing, Behavioral-Cultural Modeling and Prediction - 4th International Conference, SBP 2011, Proceedings",

note = "4th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2011 ; Conference date: 29-03-2011 Through 31-03-2011",

}

Trewhitt, E, Whitaker, E, Briscoe, E & Weiss, L 2011, Model docking using knowledge-level analysis. in Social Computing, Behavioral-Cultural Modeling and Prediction - 4th International Conference, SBP 2011, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6589 LNCS, pp. 105-112, 4th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2011, College Park, MD, United States, 3/29/11. https://doi.org/10.1007/978-3-642-19656-0_17

Model docking using knowledge-level analysis. / Trewhitt, Ethan; Whitaker, Elizabeth; Briscoe, Erica et al.
Social Computing, Behavioral-Cultural Modeling and Prediction - 4th International Conference, SBP 2011, Proceedings. 2011. p. 105-112 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6589 LNCS).

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

TY - GEN

T1 - Model docking using knowledge-level analysis

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AU - Whitaker, Elizabeth

AU - Briscoe, Erica

AU - Weiss, Lora

PY - 2011

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N2 - This paper presents an initial approach for exploring the docking of social models at the knowledge level. We have prototyped a simple blackboard environment allowing for model docking experimentation. There are research challenges in identifying which models are appropriate to dock and the concepts that they should exchange to build a richer multi-scale view of the world. Our early approach includes docking of societal system dynamics models with individual and organizational behaviors represented in agent-based models. Case-based models allow exploration of historical knowledge by other models. Our research presents initial efforts to attain opportunistic, asynchronous interactions among multi-scale models through investigation and experimentation of knowledge-level model docking. A docked system can supply a multi-scale modeling capability to support a user's what-if analysis through combinations of case-based modeling, system dynamics approaches and agent-based models working together. An example is provided for the domain of terrorist recruiting.

AB - This paper presents an initial approach for exploring the docking of social models at the knowledge level. We have prototyped a simple blackboard environment allowing for model docking experimentation. There are research challenges in identifying which models are appropriate to dock and the concepts that they should exchange to build a richer multi-scale view of the world. Our early approach includes docking of societal system dynamics models with individual and organizational behaviors represented in agent-based models. Case-based models allow exploration of historical knowledge by other models. Our research presents initial efforts to attain opportunistic, asynchronous interactions among multi-scale models through investigation and experimentation of knowledge-level model docking. A docked system can supply a multi-scale modeling capability to support a user's what-if analysis through combinations of case-based modeling, system dynamics approaches and agent-based models working together. An example is provided for the domain of terrorist recruiting.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Social Computing, Behavioral-Cultural Modeling and Prediction - 4th International Conference, SBP 2011, Proceedings

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Trewhitt E, Whitaker E, Briscoe E, Weiss L. Model docking using knowledge-level analysis. In Social Computing, Behavioral-Cultural Modeling and Prediction - 4th International Conference, SBP 2011, Proceedings. 2011. p. 105-112. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-19656-0_17

Model docking using knowledge-level analysis

Abstract

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UN SDGs

All Science Journal Classification (ASJC) codes

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