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A formal approach to protocols and strategies for (legal) negotiation
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Source International Conference on Artificial Intelligence and Law archive
Proceedings of the 8th international conference on Artificial intelligence and law table of contents
St. Louis, Missouri, United States
Pages: 168 - 177  
Year of Publication: 2001
ISBN:1-58113-368-5
Authors
Guido Governatori  Cooperative Information Systems Research Centre, Queensland University of Technology, GPO Box 2434, Brisbane QLD 4001, Australia
Marlon Dumas  Cooperative Information Systems Research Centre, Queensland University of Technology, GPO Box 2434, Brisbane QLD 4001, Australia
Arthur H. M. ter Hofstede  Cooperative Information Systems Research Centre, Queensland University of Technology, GPO Box 2434, Brisbane QLD 4001, Australia
Phillipa Oaks  Cooperative Information Systems Research Centre, Queensland University of Technology, GPO Box 2434, Brisbane QLD 4001, Australia
Sponsor
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
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ABSTRACT

We propose a formal and executable framework for expressing protocols and strategies for automated (legal) negotiation. In this framework a party involved in a negotiation is represented through a software agent composed of four modules: (i) a communication module which manages the interaction with the other agents; (ii) a control module; (iii) a reasoning module specified as a defeasible theory; and (iv) a knowledge base which bridges the control and the reasoning modules, while keeping track of past decisions and interactions. The choice of defeasible logic is justified against a set of desirable criteria for negotiation automation languages. Moreover, the suitability of the framework is illustrated through two case studies.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Agorics Inc. A survey of auctions. http://www.agorics.com/new.html, 1996.
 
2
Grigoris Antoniou, David Billington, Guido Governatori, and Michael Maher. On the modeling and analysis of regulations. In Proceedings of the Australian Conference on Information Systems, 1999.
 
3
 
4
Grigoris Antoniou, David Billington, Guido Governatori, Michael Maher, and Andrew Rock. A family of defeasible reasoning logics and its implementation. In Werner Horn, editor, ECAI 2000. Proceedings of the 14th European Conference on Artificial Intelligence, Amsterdam, 2000. IOS Press.
 
5
Grigoris Antoniou, Micheal J. Maher, and David Billington. Defeasible logic versus logic programming without negation as failure. Journal of Logic Programming, 41(1):45-57, 2000.
6
 
7
Instituto de Investigaci on en Inteligencia Artificial (IIIA). The FishMarket project. http://www.iiia.csic.es/Projects/fishmarket.
 
8
eBay. Home page. http://www.ebay.com.
 
9
A. Garcia, D. Gollapally, P. Tarau, and G. Simari. Deliberative stock market agents using Jinni and defeasible logic programming. In Proc. of the ECAI Workshop on Engineering Societies in the Agents' World, Berlin, Germany, August 2000. Springer Verlag.
 
10
Thomas F. Gordon. The Pleadings Game. Kluwer Academic Press, Dordrecht, 1995.
 
11
Guido Governatori and Michael J. Maher. An argumentation-theoretic characterization of defeasible logic. In Werner Horn, editor, ECAI 2000. Proceedings of the 14th European Conference on Artificial Intelligence,Amsterdam, 2000. IOS Press.
 
12
Guido Governatori, Michael J. Maher, Grigoris Antoniou, and David Billington. Argumentation semantics for defeasible logics. In Riichiro Mizoguchi and John Slaney, editors, PRICAI 2000: Topics in Artificial Intelligence, volume 1886 of LNAI, pages 27-37, Berlin, 2000. Springer-Verlag.
 
13
J.J. van Griethuysen, editor. Concepts and Terminology for the Conceptual Schema and the Information Base. Publ. nr. ISO/TC97/SC5/WG3-N695, ANSI, 11 West 42nd Street, New York, NY 10036, 1982.
 
14
 
15
A.H.M. ter Hofstede. Information Modelling in Data Intensive Domains. PhD thesis, University of Nijmegen, Nijmegen, The Netherlands, 1993.
 
16
IIIA, ISOCO and UPC (organizers). AMECIII trading agents' tournament. http://www.iiia.csic.es/ Projects/fishmarket/agents2000, June 2000.
 
17
N.R. Jennings, Parsons S, C. Sierra, and P. Faratin. Automated negotiation. In Proc. of the Conference on Pratical Applications of Intelligent Agents and Multi-agent Systems (PAAM), Manchester, UK, 2000.
 
18
Ronald Loui. Process and policy: resource-bounded non-demonstrative reasoning. Computational Intelligence, 14:1-38, 1998.
 
19
Michael J. Maher. Propositional defeasible logic has linear complexity. Technical report, Department of Mathematical and Computer Sciences, Loyola University, Chicago, 2000.
 
20
 
21
Michael J. Maher, Andrew Rock, Grigoris Antoniou, David Billignton, and Timothy Miller. Efficient defeasible reasoning systems. In Proc. International Conference on Tool in Artificial Intelligence. EEEI Computer Society Press, 2000.
22
 
23
Donald Nute. Apparent obligation. In Donald Nute, editor, Defeasible Deontic Logic, pages 287-316. Kluwer, 1997.
 
24
Donald Nute. Norms, priorities and defeasibility. In Paul McNamara and Henry Prakken, editors, Norms, Logics and Information Systems. New Studies in Deontic Logic, pages 83-100. IOS Press, Amsterdam, 1998.
 
25
The University of Michigan Artificial Intelligence Laboratory. The Michigan Internet AuctionBot. http://auction.eecs.umich.edu.
 
26
S. Parsons, C. Sierra, and N. Jennings. Agents that reason and negotiate by arguing. Journal of Logic and Computation, 8:261-292, 1998.
 
27
Henry Prakken. Relating protocols for dynamic dispute with logics for defeasible argumentation. Synthese, 127:187-219, 2001.
 
28
Howard Raiffa. The art and science of negotiation.Harvard University Press, Cambridge, MA, 1982.
 
29
Daniel M. Reeves, Michael P. Wellman, Benjamin N. Grosof, and Hoi Y. Chan. Automated negotiation from declarative contract descriptions. In Seventeenth National Conference on Artificial Intelligence, Workshop on Knowledge-Based Electronic Markets(KBEM), Austin, Texas, July 30-31 2000. AAAI, AAAI Press.
30
31
 
32
TradeOut. Home page. http://www.tradeout.com.
 
33
 
34
35

CITED BY  10
 
 
 
 
 
 

Collaborative Colleagues:
Guido Governatori: colleagues
Marlon Dumas: colleagues
Arthur H. M. ter Hofstede: colleagues
Phillipa Oaks: colleagues

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