Abstract
Information-based argumentation aims to model the partner’s reasoning apparatus to the extent that an agent can work with it to achieve outcomes that are mutually satisfactory and lay the foundation for continued interaction and perhaps lasting business relationships. Information-based agents take observations at face value, qualify them with a belief probability and build models solely on the basis of messages received. Using augmentative dialogue that describes what is good or bad about proposals, these agents observe such statements and aim to model the way their partners react, and then to generate dialogue that works in harmony with their partner’s reasoning.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Sierra, C., Debenham, J.: Information-based agency. In: Proceedings of Twentieth International Joint Conference on Artificial Intelligence, IJCAI 2007, Hyderabad, India, pp. 1513–1518 (2007)
Sierra, C., Debenham, J.: Trust and honour in information-based agency. In: Stone, P., Weiss, G. (eds.) Proceedings Fifth International Conference on Autonomous Agents and Multi Agent Systems AAMAS 2006, Hakodate, Japan, pp. 1225–1232. ACM Press, New York (2006)
Sierra, C., Debenham, J.: The LOGIC Negotiation Model. In: Proceedings Sixth International Conference on Autonomous Agents and Multi Agent Systems AAMAS 2007, Honolulu, Hawai’i, pp. 1026–1033 (2007)
Dung, P.M.: On the Acceptability of Arguments and its Fundamental Role in Nonmonotonic Reasoning, Logic Programming and n-Person Games. Artificial Intelligence 77, 321–358 (1995)
Rahwan, I., Ramchurn, S., Jennings, N., McBurney, P., Parsons, S., Sonenberg, E.: Argumentation-based negotiation. Knowledge Engineering Review 18, 343–375 (2003)
Cheeseman, P., Stutz, J.: On The Relationship between Bayesian and Maximum Entropy Inference. In: Bayesian Inference and Maximum Entropy Methods in Science and Engineering, pp. 445–461. American Institute of Physics, Melville (2004)
Paris, J.: Common sense and maximum entropy. Synthese 117, 75–93 (1999)
Jaynes, E.: Information theory and statistical mechanics: Part I. Physical Review 106, 620–630 (1957)
Li, Y., Bandar, Z.A., McLean, D.: An approach for measuring semantic similarity between words using multiple information sources. IEEE Transactions on Knowledge and Data Engineering 15, 871–882 (2003)
Lewicki, R.J., Saunders, D.M., Minton, J.W.: Essentials of Negotiation. McGraw Hill, New York (2001)
Bentahar, J., Mbarki, M., Meyer, J.J.C., Moulin, B.: Strategic agent communication: An argumentation-driven approach. In: Baldoni, M., Son, T.C., van Riemsdijk, M.B., Winikoff, M. (eds.) DALT 2008. LNCS (LNAI), vol. 5397, pp. 233–250. Springer, Heidelberg (2009)
Kakas, A., Maudet, N., Moraitis, P.: Layered strategies and protocols layered strategies and protocols for argumentation-based agent interaction. In: Rahwan, I., Moraïtis, P., Reed, C. (eds.) ArgMAS 2004. LNCS (LNAI), vol. 3366, pp. 64–77. Springer, Heidelberg (2005)
Mbarki, M., Bentahar, J., Moulin, B.: Specification and complexity of strategic-based reasoning using argumentation. In: Maudet, N., Parsons, S., Rahwan, I. (eds.) ArgMAS 2006. LNCS (LNAI), vol. 4766, pp. 142–160. Springer, Heidelberg (2007)
Maslow, A.H.: A theory of human motivation. Psychological Review 50, 370–396 (1943)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sierra, C., Debenham, J. (2009). Information-Based Argumentation. In: Meyer, JJ.C., Broersen, J. (eds) Knowledge Representation for Agents and Multi-Agent Systems. KRAMAS 2008. Lecture Notes in Computer Science(), vol 5605. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05301-6_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-05301-6_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-05300-9
Online ISBN: 978-3-642-05301-6
eBook Packages: Computer ScienceComputer Science (R0)