Representative Publications of Dr. Thomas/Tom Wagner


Preface

This page contains links to representative publications. Representative publications fall into several categories, though my basic research focus is in control of complex problem solving agents. My most recent focus is in control for large-scale multi-agent systems. Click here to take you to my most recent coordination work and Click here to take you to my most recent application work.

 

Application Examples and Demonstration Vehicles

 

Research Software Engineering Notes

  • Thomas Wagner, Bryan Horling, Victor Lesser, John Phelps, and Valerie Guralnik, "The Struggle for Reuse: Pros and Cons of Generalization in TAEMS and Its Impact on Technology Transition," 12th International Conference on Intelligent and Adaptive Systems and Software Engineering (IASSE-2003), San Francisco, CA, USA, 2003.
    Paper is available in [ Acrobat PDF format, size is 720k ]

  • Thomas Wagner and Bryan Horling, "The Struggle for Reuse and Domain Independence: Research with TÆMS, DTC, and JAF," 2nd Annual International Workshop on Infrastructure for Agents, MAS, and Scalable Multi-Agent Systems, 2001.
    Paper is available in [ Acrobat PDF format, size is 264 k ]   [ Postscript format, size is 220 k ]

 

Soft Real-Time Agent Control

Papers in this category focus on the Design-to-Criteria agent scheduler, aka DTC. DTC is an analysis component that enables the agent to plan to meet time, cost, and resource constraints and to perform this planning in soft real time. This is how complex problem solving agents can adapt to different circumstances and different situations, online, as the environment changes and interactions with other agents change the local agent's control problem space.

  • Thomas Wagner, Anita Raja, and Victor Lesser, "Modeling Uncertainty and its Implications to Sophisticated Control in TAEMS Agents," Under review, 2003.
    Paper is available in [ Acrobat PDF format, size is 784 k ]

  • Bryan Horling, Victor Lesser, Regis Vincent and Thomas Wagner, "The Soft Real-Time Agent Framework," Under Review, 2003.
    Paper is available in [ Acrobat PDF format, size is 960 k ]

  • Thomas Wagner and Victor Lesser, "Toward Soft Real-Time Agent Control," Lecture Notes in Computer Science: Infrastructure for Large-Scale Multi-Agent Systems, Wagner/Rana editors, Springer-Verlag, 2001.
    Paper is available in [ Acrobat PDF format, size is 620 k ]   [ Postscript format, size is 908 k ]

  • Thomas Wagner, Alan Garvey, and Victor Lesser, "Criteria Directed Task Scheduling," Appears in the Special Scheduling Issue of the Journal for Approximate Reasoning, vol 19, number 1-2, pages 91-118, 1998.
    Paper is available in [ Acrobat PDF format, size is 1080 k ]

  • Anita Raja, Victor Lesser, and Thomas Wagner, "Toward Robust Agent Control in Open Environments," Proceedings of the 4th International Conference on Autonomous Agents (Agents-2000), June, 2000.
    Paper coming soon.

  • John Phelps and Thomas Wagner, "Knowledge-Based Task Structure Generation for a Real-Time Information Gathering Agent," Proceedings of the 5th World Multiconference on Systemics, Cybernetics and Informatics (SCI 2001) and the 7th International Conference on Information Systems Analysis and Synthesis (ISAS 2001), July, 2001. Winner of the Best Paper award for its division of the conference.
    Paper coming soon.

  • Regis Vincent, Bryan Horling, Victor Lesser, and Thomas Wagner, "Implementing Soft Real-Time Agent Control," Proceedings of the 5th International Conference on Autonomous Agents (Agents-2001), May, 2001.
    Paper is available in [ Acrobat PDF format, size is 192 k ]   [ Postscript format, size is 924 k ]

  • Also see below for the paper on integrating control at this level with organizational level control.

 

Soft Real-Time Agent Control for Large Scale MAS

Papers in this category focus on the Motivational Quantities or MQ framework. The MQ framework builds on work in DTC and TAEMS (Decker 94 to Lesser et al 2001) enables complex agents to represent and reason about their organizational situation. The MQ framework models, for instance, agents having conflicting organizational goals and the quantitative implications of selecting goals to pursue. The framework also models tasks that are performed for cooperative reasons, self interested reasons, or ranges of these.

Papers that deal with the use of the MQ model in multi-agent negotiation are here.

 

Negotiation with the MQ Model

Papers in this class focus on the role of the MQ model in agent negotiation. From a high-level, the model gives the agents the ability to compare self-interested motivations to cooperative motivations and to reason about motivations between these extremes.

Information on the MQ framework itself is here.

 

Coordination Centered Control Issues

Papers in this class focus on the coordination problem and how the process of coordinating multiple agents interacts with the local control problem solving of individual agents.

Papers that deal with multi-agent negotiation via the MQ model are here. Papers on the MQ model itself are here.

 


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