Automated Negotiation from Declarative Contract Descriptions

Our approach for automating the negotiation of business contracts proceeds in three broad steps. First, determine the structure of the negotiation process by applying general knowledge about auctions and domain–specific knowledge about the contract subject along with preferences from potential buyer...

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Podrobná bibliografia
Vydané v:	Computational intelligence Ročník 18; číslo 4; s. 482 - 500
Hlavní autori:	Reeves, Daniel M., Wellman, Michael P., Grosof, Benjamin N.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Boston, USA and Oxford, UK Blackwell Publishers Inc 01.11.2002
Predmet:	auctions automated negotiation declarative knowledge representation e-commerce electronic contracting rule-based programming situated courteous logic programs
ISSN:	0824-7935, 1467-8640
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Popis
Shrnutí:	Our approach for automating the negotiation of business contracts proceeds in three broad steps. First, determine the structure of the negotiation process by applying general knowledge about auctions and domain–specific knowledge about the contract subject along with preferences from potential buyers and sellers. Second, translate the determined negotiation structure into an operational specification for an auction platform. Third, after the negotiation has completed, map the negotiation results to a final contract. We have implemented a prototype which supports these steps by employing a declarative specification (in courteous logic programs) of (1) high–level knowledge about alternative negotiation structures, (2) general–case rules about auction parameters, (3) rules to map the auction parameters to a specific auction platform, and (4) special–case rules for subject domains. We demonstrate the flexibility of this approach by automatically generating several alternative negotiation structures for the domain of travel shopping in a trading agent competition.
Bibliografia:	ark:/67375/WNG-DCMQDZX6-H ArticleID:COIN199 istex:9255DE1B90F7A807644DBB867010C94E4638356F
ISSN:	0824-7935 1467-8640
DOI:	10.1111/1467-8640.00199