Abstract
Case-Based Reasoning (CBR) can give agents the capability of learning from their own experience and solve new problems, however, in a multi-agent system, the ability of agents to collaborate is also crucial. In this paper we present an argumentation framework (AMAL) designed to provide learning agents with collaborative problem solving (joint deliberation) and information sharing capabilities (learning from communication). We will introduce the idea of CBR multi-agent systems (\(\mathcal{M}{\normalfont \textsf{AC}}\) systems), outline our argumentation framework and provide several examples of new tasks that agents in a \(\mathcal{M}\normalfont \textsf{AC}\) system can undertake thanks to the argumentation processes.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Aamodt, A., Plaza, E.: Case-based reasoning: Foundational issues, methodological variations, and system approaches. Artificial Intelligence Communications 7(1), 39–59 (1994)
Amgoud, L., Serrurier, M.: Arguing and explaining classifications. In: Rahwan, I., Parsons, S., Reed, C. (eds.) Argumentation in Multi-Agent Systems. LNCS (LNAI), vol. 4946, pp. 164–177. Springer, Heidelberg (2008)
Brewka, G.: Dynamic argument systems: A formal model of argumentation processes based on situation calculus. Journal of Logic and Computation 11(2), 257–282 (2001)
Chesñevar, C.I., Simari, G.R.: Formalizing Defeasible Argumentation using Labelled Deductive Systems. Journal of Computer Science & Technology 1(4), 18–33 (2000)
Fukumoto, T., Sawamura, H.: Argumentation-based learning. In: Maudet, N., Parsons, S., Rahwan, I. (eds.) ArgMAS 2006. LNCS (LNAI), vol. 4766, pp. 17–35. Springer, Heidelberg (2007)
Leake, D., Sooriamurthi, R.: Automatically selecting strategies for multi-case-base reasoning. In: Craw, S., Preece, A.D. (eds.) ECCBR 2002. LNCS (LNAI), vol. 2416, pp. 204–219. Springer, Heidelberg (2002)
Martín, F.J., Plaza, E., Arcos, J.-L.: Knowledge and experience reuse through communications among competent (peer) agents. International Journal of Software Engineering and Knowledge Engineering 9(3), 319–341 (1999)
McGinty, L., Smyth, B.: Collaborative case-based reasoning: Applications in personalized route planning. In: Aha, D.W., Watson, I., Yang, Q. (eds.) ICCBR 2001. LNCS (LNAI), vol. 2080, pp. 362–376. Springer, Heidelberg (2001)
Možina, M., Žabkar, J., Bratko, I.: Argument based machine learning. machine learning 171, 922–937 (2007)
Ontañón, S., Plaza, E.: Learning and joint deliberation through argumentation in multi-agent systems. In: Proc. AAMAS 2007, pp. 971–978. ACM, New York (2007)
Plaza, E., Ontañón, S.: Learning collaboration strategies for committees of learning agents. Journal of Autonomous Agents and Multi-Agent Systems 13, 429–461 (2006)
Nagendra Prassad, M.V., Lesser, V.R., Lander, S.: Retrieval and reasoning in distributed case bases. Technical report, UMass Computer Science Department (1995)
Sycara, K., Kraus, S., Evenchik, A.: Reaching agreements through argumentation: a logical model and implementation. Artificial Intelligence Journal 104, 1–69 (1998)
Jennings, N.R., Parsons, S., Sierra, C.: Agents that reason and negotiate by arguing. Journal of Logic and Computation 8, 261–292 (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ontañón, S., Plaza, E. (2008). Learning, Information Exchange, and Joint-Deliberation through Argumentation in Multi-agent Systems. In: Meersman, R., Tari, Z., Herrero, P. (eds) On the Move to Meaningful Internet Systems: OTM 2008 Workshops. OTM 2008. Lecture Notes in Computer Science, vol 5333. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88875-8_34
Download citation
DOI: https://doi.org/10.1007/978-3-540-88875-8_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88874-1
Online ISBN: 978-3-540-88875-8
eBook Packages: Computer ScienceComputer Science (R0)