Exploring the Strategy Space of Negotiating Agents: A Framework for Bidding, Learning and Accepting in Automated Negotiation

Publication Type:



Tim Baarslag


Springer Theses: Recognizing Outstanding Ph.D. Research, Springer International Publishing (2016)






Acceptance, ANAC, automated negotiation, Bidding, Concessions, Genius, Learning techniques, Machine Learning, Negotiation, Opponent model, Opponent modeling, Software agents


<p>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.</p>