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Exploring the Strategy Space of Negotiating Agents [electronic resource] : A Framework for Bidding, Learning and Accepting in Automated Negotiation / by Tim Baarslag.

By: Baarslag, Tim [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Springer Theses, Recognizing Outstanding Ph.D. Research: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2016Edition: 1st ed. 2016.Description: XXI, 276 p. 58 illus., 37 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319282435.Subject(s): Engineering | Artificial intelligence | Robotics | Automation | Economic theory | Engineering | Robotics and Automation | Artificial Intelligence (incl. Robotics) | Economic Theory/Quantitative Economics/Mathematical MethodsAdditional physical formats: Printed edition:: No titleDDC classification: 629.892 Online resources: Click here to access online
Contents:
Introduction -- Background -- A Component-based Architecture to Explore the Space of Negotiation Strategies -- Effective Acceptance Conditions -- Accepting Optimally with Incomplete Information -- Measuring the Performance of Online Opponent Models -- Predicting the Performance of Opponent Models -- A Quantitative Concession-Based Classification Method of Bidding Strategies -- Optimal Non-adaptive Concession Strategies -- Putting the Pieces Together -- Conclusion.
In: Springer eBooksSummary: This book reports on an outstanding thesis that has significantly advanced the state-of-the-art in the area of automated negotiation. It gives new practical and theoretical insights into the design and evaluation of automated negotiators. It describes an innovative negotiating agent framework that enables systematic exploration of the space of possible negotiation strategies by recombining different agent components. Using this framework, new and effective ways are formulated for an agent to learn, bid, and accept during a negotiation. The findings have been evaluated in four annual instantiations of the International Automated Negotiating Agents Competition (ANAC), the results of which are also outlined here. The book also describes several methodologies for evaluating and comparing negotiation strategies and components, with a special emphasis on performance and accuracy measures.
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Introduction -- Background -- A Component-based Architecture to Explore the Space of Negotiation Strategies -- Effective Acceptance Conditions -- Accepting Optimally with Incomplete Information -- Measuring the Performance of Online Opponent Models -- Predicting the Performance of Opponent Models -- A Quantitative Concession-Based Classification Method of Bidding Strategies -- Optimal Non-adaptive Concession Strategies -- Putting the Pieces Together -- Conclusion.

This book reports on an outstanding thesis that has significantly advanced the state-of-the-art in the area of automated negotiation. It gives new practical and theoretical insights into the design and evaluation of automated negotiators. It describes an innovative negotiating agent framework that enables systematic exploration of the space of possible negotiation strategies by recombining different agent components. Using this framework, new and effective ways are formulated for an agent to learn, bid, and accept during a negotiation. The findings have been evaluated in four annual instantiations of the International Automated Negotiating Agents Competition (ANAC), the results of which are also outlined here. The book also describes several methodologies for evaluating and comparing negotiation strategies and components, with a special emphasis on performance and accuracy measures.

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