A Classification Structure for Automated Negotiations

2006 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2006 Workshops Proceedings), Hong Kong, China

A Classification Structure for Automated Negotiations Ricardo Büttner Information Systems II, Institute of Business Administration University of Hohenheim, 70593 Stuttgart, Germany [email protected]

Abstract

literature investigation of negotiation phenomena of organizational approaches in economics.

To date, a lot of automated negotiation models have been developed and manifold negotiation challenges have been already addressed. However, in order to evaluate the state of the art of automated negotiations a classification structure is needed. This paper proposed a taxonomy for classifying automated negotiations. The evaluation of the state of the art to this taxonomy shows the manifold addressing of negotiation challenges, but mainly related to the structure and the process of the negotiation. However, criteria of theoretic foundations and specific negotiation phenomena seem to be inadequately researched.

2. Classifying Automated Negotiations The paper mainly analyzed the works [6, 8, 38, 64, 73, 81, 83, 100, 113, 134, 138]. The main criteria for classifying automated negotiations can be summarized as follows (Fig. 1):

1. Motivation and Problem Description Electronic commerce, particularly automated negotiations, are phenomenal growing fields, e. g. [37, 39, 65, 66, 93]. Systems in these fields have to implement real business requirements that are increasing as well. To date, a lot of automated negotiation models have been developed and manifold negotiation challenges have been addressed. However, in order to evaluate the state of the art of automated negotiations, a classification structure is needed. The research has shown different criteria for classifying automated negotiations [100]. That is why this paper identifies the main criteria to classify automated negotiations and proposes a consolidated criteria structure. This structure is useful for evaluating the research status as well as for giving an overview, especially to new researcher in the field of E-Commerce. The paper is separated into 3 parts: After the problem description, the following part 2 analyzes the main criteria for classifying automated negotiations on the basis of a literature investigation and makes a proposal for a consolidated criteria structure. Part 3 identifies the future need for research based on a reflection of the negotiation models that have been developed to date. The reflection is based on a

Figure 1. Main criteria for classifying Automated Negotiations

2.1. Criteria for the Negotiation Structure One of the most common criteria is the protocol category. It describes the number of negotiating partners [8, 84]. There, bilateral, one-sided multilateral and double-sided multilateral negotiations are separated [83]. Bilateral automated negotiations between self interested

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agents were first analyzed by [87, 88, 144] on the basis of [130]. This type is restricted to two negotiation partners (one buyer and one seller). At first view, it seems to be a very simple negotiation situation. But the trial to integrate real world phenomena (for instance private information or fraud) makes these kind of negotiations very complex [45, 83]. In contrast, one-sided multilateral negotiations (e. g., [41, 122] or ICOMA Auction [61]) are either characterized by one seller and many buyers or by many sellers and one buyer [83, p. 611]. This type of negotiation is deemed to be the standard form of auctions [64, p. 37]. Double-sided multilateral negotiations are characterized by many buyers and many sellers (e. g., [137] based on [88], [125] based on [57] or [142]).

characterized by a direct communication between the participants, e. g., DiCarta [25] or INSPIRE/INSS [43, 44]. In a mediated negotiation, a broker (intermediator) supports the negotiation process or the negotiating partners, for example [10, 34, 48, 58, 80, 120, 125]. In addition, the broker can also control the market process [19].

Concerning the distribution type, automated negotiations can be differentiated in distributed and integrated models [42, 131, 134]. In case of the distributed model, every negotiation partner tries to maximize his own utility (win-lose approach). In contrast, the target of integrated models is to maximize the collective utility of all partners (win-win approach).

Despite of the fact, that the automating of negotiations was forecasted by [22] more than 20 years ago, the question of the possible automation level is still discussed in a very controversial way [6, 45, 79]. The state of the art in electronic negotiations shows full-automated, process support and hybrid negotiation models [83]. Fullautomated models are well structured in order to give the software agents the possibility to negotiate autonomously [8, p. 320]. This type of negotiation is result-oriented. In contrast, process support models facilitate the negotiation (e. g., INSPIRE/INSS [43, 44], CrossFlow [49], CBSS [140] or http://www.ebay.com/). Here, the human participants make the final decision regarding the negotiation result. Concerning the support models, M. Schoop et al. [101] differentiated between document- and communication-oriented approaches. Communication-oriented approaches support the communicative processes involved in any negotiation. Document-oriented approaches offer the possibilities for document exchange and document management. But, e. g., the negotiation support system Negoisst [101] combines both approaches. Finishing, hybrid models are partly-automated, e. g., [1, 23, 123, 139].

Attributes are the characteristics of the negotiation item, that are taken into account during the evaluation. There are two attribute types: single- and multi-attribute. In a single-attribute negotiation the negotiation item is evaluated by one characteristic, normally the price. All other attributes, for instance quality or warranty, have to be agreed in advance. They are not negotiated. Single-attribute negotiations are shown by [29, 41, 120]. In contrast, multi-attribute negotiations are the regular case in non-electronic commercial everyday life [83, p. 612]. This type of negotiation takes simultaneous more than one characteristic into account, e. g., [1, 7, 24, 25, 30, 31, 32, 33, 43, 44, 46, 50, 51, 58, 85, 115, 125, 143]. The number of positions describes the quantity of independent items in a single negotiation over there a final decision is made. The number of positions is independent to the number of attributes or the volume. Automated negotiation systems with the possibility to contract a high number of positions are of significant practical relevance [9, 47]. To solve the complexity problem caused by a high number of positions, normally bidding or auction packages are manually defined in order to get a combined product package, for example Quotes [86] or [63]. In the research area, most of the automated negotiation models do not support a high number of positions [83, p. 613], exceptions are: [2, 5, 11, 23, 115, 121, 122]. Furthermore, negotiations can be separated regarding their mediation type: A non-mediated negotiation is

Regarding the access type, a negotiation can be separated in public and closed sessions [8, p. 318]. In public negotiations new participants can take part dynamically. That is not allowed in closed sessions.

2.2. Describing the Negotiation Process

Regarding the orientation type, [134] presented a differentiation concerning the negotiation process. There, norm-oriented and goal-oriented negotiations are distinguished. Norm-oriented negotiations are characterized by negotiators who act on the basis of obligations and social commitments resulting from negotiation steps. In contrast, the goal-based form is marked by negotiators who act on the basis of expressed goals and objectives. Furthermore, electronic negotiations can be distinguished by the binding type. Binding negotiations (e. g., http://www.ebay.com/) need an authentication of every participant in advance [6, p. 248]. T. W. Sandholm and V. R. Lesser analyzed binding negotiations in [96, 97]



and presented the so called LCCP (Leveled Commitment Contracting Protocol). LCCP allows a participant to broke a commitment unilaterally. There, the commitments vary continuously from unbreakable to breakable. To every commitment, specific breaking costs are assigned. For example, LCCP is used in the system eMediator [95]. In contrast to binding negotiations, non-binding negotiations do not need an authentication.

negotiation process. One of the strongest advantages of argumentation-based approaches is the ability of an agent to evaluate and possibly correct their own point of view by using the arguments of the negotiation partner [136, p. 148 f.]. Further, the ABN approach increases the possibility and the quality of an agreement compared to the game-theoretic or the heuristic approach [40, 81].

2.4. Criteria for Restrictions 2.3. Theoretic Foundation Criteria [37, 38, 81] differentiate automated negotiations regarding their theoretical approach: game-theoretic, heuristic and argumentation-based approaches are separated. The game-theoretic approach tries to find the optimal strategy between identical agents by the analysis of the equilibrium conditions [56, 70, 71, 72, 99, 102, 103]. On the basis of the fundamental game-theoretic work [130] by J. L. von Neumann and O. Morgenstern, J. S. Rosenschein and G. Zlotkin were the first who analyzed strategic interactions between self-interested agents [87, 88, 144]. Their formal analysis is based on the distributed problem solving approach (see [13]) based on the work of J. C. Harsanyi et al. [35, 36] and D. M. Kreps et al. [55]. Game-theoretic models are deemed to be mathematically elegant, but are very restricted in use because of their assumptions of perfect rationality, unlimited resources and a perfect information situation [21, 37, 39, 74, 78]. Heuristic approaches solve the problematic assumption of unlimited resources via thumb rules, for example [27, 52]. There, the results do normally not correspond to the optimal solutions. Thus, the assumption of perfect rationality is also rejected. Automated negotiation models based on heuristic approaches need an intensive evaluation, regular via simulation or empirical analyses [37, p. 210]. In game-theoretic or heuristic approaches, agents transfer only one information characteristic: offers in terms of potential agreements. In contrast, in argumentationbased negotiations (ABN), the agents have the possibility to reason their positions. When the negotiation partner is persuaded, he will change his negotiation position. The argumentation-based approach was first realized by K. P. Sycara in the negotiation support system PERSUADER [116, 117, 118, 119]. PERSUADER tries to resolve target conflicts between agents by using historical information to persuade the negotiation partner. S. Parsons et al. developed an argumentation-based negotiation model in [76, 77]. The implementation of the model and the design of the different mental attitudes (see belief-desires-intentions model [14]) were shown by [91]. In [106, 107], C. Sierra et al. showed how arguments can be integrated in the general

A. R. Lomuscio et al. [64] differentiate in their classification scheme between complete and incomplete information situations. But, the incompleteness of information is only related to the negotiation partner. For example, the time limit of the negotiation process or the utility function of the negotiation partner can be modeled as private [64, p. 38]. As first, [88] analyzed scenarios with incomplete information. D. Neumann et al. [73] differentiate the information situation related to the negotiation item (open versus closed order books). [17] distinguished incomplete information and/or information circumstances fraught with risk regarding the negotiation item, the negotiation partner and the environment. Time has enormous influence to negotiations [114]: At first, S. Kraus et al. [54] took time limits into account in automated negotiations. Accordingly, e. g., [4, 29, 30, 31, 32, 58, 125, 132, 133] include time limits in their negotiation models. Besides the duration of the negotiation process, timing plays an important role in (automated) negotiations [110].

3. Summary and Future Research Directions Through the increasing importance of electronic markets [64, 105, 145], the requirements of automated negotiation systems increase significantly. The results of this paper show the manifold addressing of negotiation challenges, but mainly related to the structure and the process of the negotiation. However, criteria of theoretic foundations and specific negotiation phenomena seem to be inadequate researched. To address this point, a reflection of negotiation phenomena of organizational approaches seem to be reasonable.

3.1. Direction A: Bounded Rationality The concept of bounded rationality by H. A. Simon [108] is a basic assumption of the most microeconomic organizational approaches (extensions of game theory [90, 92, 112], behavioral-decision-theory [109, 127, 128], systemoriented approach [129], principal-agent-theory [89]). In principle, the main cause of bounded rationality is the



limitation of resources: E. g., [59, 126, 132] restricted the computational resources, [125] assumed communication costs and [12] information costs above zero. In general, bounded rationality can be modeled via simplifications: Most of the approaches related to bounded rationality, model these by heuristics or rather rules of thumb, e. g., [3, 16, 28, 53, 82, 124, 69, 94, 104, 143]. [98, 142] used heuristic search algorithms, [41, 104] heuristic biddingstrategies. [18] used heuristics based on genetic algorithms. In [90], bounded rationality was modeled by the explicit reduction of the negotiation process. [7] modeled bounded rationality through a predefined utility function. Another way to represent bounded rationality was provided by probability-based models, for example [75, 132]. Finally, the fuzzy approach [141] also presents a possibility for simplifications, e. g., [67, 133]. To date, most of the automated negotiation work have focussed on modeling of bounded rationality by heuristics in order to simplify real world phenomena. But in fact, automated negotiation systems have to handle with strategic behavior of the negotiation partner in spite of bounded rationality or rather limited computational resources. There is a future need of research for new models.

3.2. Direction B: Imperfect Information Although the mathematical-normative branch of the decision-oriented approach [60] and basic works of game theory [130] assume perfect information and thus a decision situation of certainty, the result of the reflection shows that the majority of the organizational approaches (behavioraldecision-theory [20, 68], system-oriented approach [129], transaction-costs-theory [135], principal-agent-theory [89] and extensions of game theory [35, 55]) imply an incomplete and/or an information situation of uncertainty. Despite of the fact, that imperfect information situations play an important role, most of the automated negotiation works have focussed only on the negotiation partner [17]. The negotiation object and the negotiation environment have been inadequate considered, exemplary exceptions: [15, 69, 58, 67, 126]. The handling of incomplete or uncertain information situations related to the negotiation object or the negotiation environment should be a future research direction within the field of automated negotiations.

References [1] M. Addis, P. Allen, and M. Surridge. Negotiating for Software Services. In DEXA ’00: Proceedings of the 11th International Workshop on Database and Expert Systems Applications (DEXA’00) [24], pages 1039–1050.

[2] S. Airiau and S. Sen. Strategic Bidding for Multiple Units in Simultaneous and Sequential Auctions. Group Decision and Negotiation, 12(5):397–413, September 2003. [3] R. Azoulay-Schwartz and S. Kraus. Negotiation on Data Allocation in Multi-Agent Environments. Autonomous Agents and Multi-Agent Systems, 5(2):123–172, 2002. [4] M. Bac. On Creating and Claiming Value in Negotiations. Group Decision and Negotiation, 10(3):234–251, May 2001. [5] M. Barbuceanu and W.-K. Lo. Multi-Attribute Utility Theoretic Negotiation for Electronic Commerce. In Dignum and Cortés [26], pages 15–30. [6] C. Beam, A. Segev, M. Bichler, and R. Krishnan. On Negotiations and Deal Making in Electronic Markets. Information Systems Frontiers, 1(3):241–258, 1999. [7] M. Bichler. Trading Financial Derivatives on the Web – An Approach Towards Automating Negotiations on OTC Markets. Information Systems Frontiers, 1(4):401–414, 2000. [8] M. Bichler, G. E. Kersten, and S. Strecker. Towards a Structured Design of Electronic Negotiations. Group Decision and Negotiation, 12(4):311–335, July 2003. [9] M. Bichler, A. Pikovsky, and T. Setzer. Kombinatorische Auktionen in der betrieblichen Beschaffung - Eine Analyse grundlegender Entwurfsprobleme. Wirtschaftsinformatik, 47(2):126–134, April 2005. WI - State of the Art. [10] M. Bichler, A. Segev, and C. Beam. An Electronic Broker for Business-To-Business Electronic Commerce on the Internet. International Journal of Cooperative Information Systems (IJCIS), 7(4):315–330, 1998. [11] M. Bichler and H. Werthner. A Classification Framework of Multidimensional, Multi-Unit Procurement Negotiations. In DEXA ’00: Proceedings of the 11th International Workshop on Database and Expert Systems Applications (DEXA’00) [24], pages 1003–1009. [12] T. Blecker, N. Abdelkafi, G. Kreutler, and B. Kaluza. Auction-based Variety Formation and Steering for Mass Customization. Electronic Markets, 14(3):232–242, September 2004. [13] A. H. Bond and L. Gasser. An Analysis of Problems and Research in DAI. In A. H. Bond and L. Gasser, editors, Readings in Distributed Artificial Intelligence, pages 3–35. Morgan Kaufmann Publishers, San Mateo, CA, 1988. [14] M. E. Bratman, D. J. Israel, and M. E. Pollack. Plans and Resource-Bounded Practical Reasoning. Computational Intelligence, 4(4):349–355, 1988. [15] M. Budimir and P. Gomber. Dynamische Marktmodelle im elektronischen Wertpapierhandel. Wirtschaftsinformatik, 41(3):218–225, Juni 1999. [16] T. Bui, J. Yen, J. Hu, and S. Sankaran. A Multi-Attribute Negotiation Support System with Market Signaling for Electronic Markets. Group Decision and Negotiation, 10(6):515–537, November 2001. [17] R. Büttner. The State of the Art in Automated Negotiation Models of the Behavior and Information Perspective. International Transactions on Systems Science and Applications (ITSSA), 1(4):351–356, September 2006. Special Issue Section of the Fourth German Conference on MultiAgent System Technologies (MATES06) Selected Papers, 19.-20. September 2006, Erfurt, Germany.



[18] A. Cardon, T. Galinho, and J.-P. Vacher. Genetic algorithms using multi-objectives in a multi-agent system. Robotics and Autonomous Systems, 33(2-3):179–190, November 2000. [19] J. Collins, M. Tsvetovatyy, B. Mobasher, and M. Gini. MAGNET: A Multi-Agent Contracting System for Plan Execution. In Proceedings of Workshop on Artificial Intelligence and Manufacturing: State of the Art and State of Practice, pages 63–68, Albuquerque, New Mexico, 31. August - 2. September 1998. AAAI Press. [20] R. M. Cyert and J. G. March. A Behavioral Theory of the Firm. Prentice-Hall, Englewood Cliffs, New Jersey, 1963. [21] R. K. Dash, D. C. Parkes, and N. R. Jennings. Computational Mechnism Design: A Call to Arms. IEEE Intelligent Systems, 18(6):40–47, November / December 2003. [22] R. Davis and R. G. Smith. Negotiation as a Metaphor for Distributed Problem Solving. Artificial Intelligence, 20(1):63–109, January 1983. [23] G. E. de Paula, F. S. Ramos, and G. L. Ramalho. Bilateral Negotiation Model for Agent Mediated Electronic Commerce. In Dignum and Cortés [26]. [24] DEXA. 11th International Workshop on Database and Expert Systems Applications (DEXA’00), Greenwich, London, UK, 6-8 September 2000. IEEE Computer Society. [25] diCarta, Inc. diCarta Contracts Version 6. http://www.dicarta.com (27.12.2004). [26] F. P. M. Dignum and U. Cortés, editors. Agent-Mediated Electronic Commerce III: Current Issues in Agent-Based Electronic Commerce Systems. Number 2003 in Lecture Notes in Artificial Intelligence (LNAI). Springer-Verlag, Berlin / Heidelberg / New York, 2001. [27] P. Faratin. Automated Service Negotiation between Autonomous Computational Agents. PhD thesis, University of London, Queen Mary and Westfield College, Department of Electronic Engineering, December 2000. [28] P. Faratin, C. Sierra, and N. R. Jennings. Using similarity criteria to make issue trade-offs in automated negotiations. Artificial Intelligence, 142(2):205–237, 2002. [29] S. S. Fatima, M. Wooldridge, and N. R. Jennings. Optimal Negotiation Strategies for Agents with Incomplete Information. In Proc. 8th Int. Workshop on Agent Theories, Architectures and Languages (ATAL), pages 53–68, Seattle, USA, 2001. [30] S. S. Fatima, M. Wooldridge, and N. R. Jennings. Multiissue negotiation under time constraints. In Proceedings of the First International Conference on Autonomous Agents and Multiagent Systems (AAMAS-02), pages 143– 150. ACM Press, 2002. [31] S. S. Fatima, M. Wooldridge, and N. R. Jennings. Optimal Agendas for Multi-Issue Negotiation. In Proceedings of the Second International Conference on Autonomous Agents and Multiagent Systems (AAMAS-03), pages 129– 136. ACM Press, 2003. [32] S. S. Fatima, M. Wooldridge, and N. R. Jennings. An agenda-based framework for multi-issue negotiation. Artificial Intelligence, 152(1):1–45, 2004. [33] R. H. Guttman, F. Viegas, and A. F. I. Kleiner. Tête-à-tête (1997-2000). http://xenia.media.mit.edu/ guttman/research/tete/tete.html (27.12.2004), 2000.

[34] C. Hanachi and C. Sibertin-Blanc. Protocol Moderators as Active Middle-Agents in Multi-Agent Systems. Autonomous Agents and Multi-Agent Systems, 8(2):131–164, 2004. [35] J. C. Harsanyi. Games with Incomplete Information Played by ’Bayesian’ Players, I: The Basic Model. Management Science, 14(3):159–182, November 1967. [36] J. C. Harsanyi and R. Selten. A generalized Nash solution for two-person bargaining games with incomplete information. Management Science, 18(5):80–106, January 1972. [37] N. R. Jennings, P. Faratin, A. R. Lomuscio, S. Parsons, C. Sierra, and M. Wooldridge. Automated Negotiation: Prospects, Methods and Challenges. Group Decision and Negotiation, 10(2):199–215, 2001. [38] N. R. Jennings, S. Parsons, C. Sierra, and P. Faratin. Automated Negotiation. Proceedings of the 5th International Conference on the Practical Application of Intelligent Agents and Multi-Agent Technology (PAAM 2000), pages 23–30, Manchester, UK, 2000. [39] N. R. Jennings, K. Sycara, and M. Wooldridge. A Roadmap of Agent Research and Development. Autonomous Agents and Multi-Agent Systems, 1(1):7–38, 1998. [40] N. C. Karunatillake and N. R. Jennings. Is it Worth Arguing? In First International Workshop on Argumentation in Multi-Agent Systems (ArgMAS 2004), pages 62–77, Columbia University, NY, USA, July 2004. [41] D. D. Kehagias, A. L. Symeonidis, and P. A. Mitkas. Designing Pricing Mechanism for Autonomous Agents Based on Bid-Forecasting. Electronic Markets, 15(1):53–62, February 2005. [42] G. E. Kersten. Modeling Distributive and Integrative Negotiations: Review and Revised Characterization. Group Decision and Negotiation, 10(6):493–514, November 2001. [43] G. E. Kersten and S. J. Noronha. Supporting International Negotiations with a WWW-based System, August 1997. Interim Report 97-49, International Institute for Applied Systems Analysis (IIASA), Austria. [44] G. E. Kersten and S. J. Noronha. Negotiation and the Web: User’s Perceptions and acceptance, March 1998. Interim Report IR-98-002, International Institute for Applied Systems Analysis (IIASA), Austria. [45] G. E. Kersten, S. J. Noronha, and J. Teich. Are All ECommerce Negotiations Auctions?, 1999. Interneg Interim Report INR08/99, International Institute for Applied Systems Analysis (IIASA), Austria. [46] M. Khedr and A. Karmouch. Negotiating Context Information in Context-Aware Systems. IEEE Intelligent Systems, 19(6):21–29, 2004. [47] M. Klein, P. Faratin, H. Sayama, and Y. Bar-Yam. Negotiating Complex Contracts. Group Decision and Negotiation, 12(2):111–125, March 2003. [48] M. Klein, P. Faratin, H. Sayama, and Y. Bar-Yam. Protocols for Negotiating Complex Contracts. IEEE Intelligent Systems, 18(6):32–38, November/December 2003. [49] M. Koetsier, P. W. P. J. Grefen, and J. Vonk. Contracts for Cross-Organizational Workflow Management. In EC-WEB ’00: Proceedings of the First International Conference on Electronic Commerce and Web Technologies, pages 110– 121. Springer-Verlag, 2000.



[50] R. Kowalczyk and V. Bui. On Fuzzy e-Negotiation Agents: Autonomous Negotiation with Incomplete and Imprecise Information. In DEXA ’00: Proceedings of the 11th International Workshop on Database and Expert Systems Applications, page 1034. IEEE Computer Society, 2000. [51] R. Kowalczyk and V. Bui. On Constraint-Based Reasoning in e-Negotiation Agents, pages 31–46. In Dignum and Cortés [26], 2001. [52] S. Kraus. Strategic Negotiation in Multi-Agent Environments. MIT Press, Cambridge, MA, USA, 2001. [53] S. Kraus, K. Sycara, and A. Evenchik. Reaching agreements through argumentation: a logical model and implementation. Artificial Intelligence, 104(1-2):1–69, 1998. [54] S. Kraus, J. Wilkenfeld, and G. Zlotkin. Multiagent negotiation under time constraints. Artificial Intelligence, 75(2):297–345, 1995. [55] D. M. Kreps, P. R. Milgrom, J. Roberts, and R. B. Wilson. Rational Cooperation in the Finitely Repeated Prisoners’ Dilemma. Journal of Economic Theory, 27(2):245–252, August 1982. [56] D. M. Kreps and R. B. Wilson. Sequential equilibria. Econometrica, 50(4):863–894, July 1982. [57] K. Kurbel and I. Loutchko. Multi-agent Negotiation under Time Constraints on an Agent-based Marketplace for Personnel Acquisition. In T. Dittmar, B. Franczyk, and R. Hofmann, editors, Proceedings of the 3rd International Symposium on Multi-Agent Systems, Large Complex Systems, and E-Business (MALCEB 2002), pages 566–579, Erfurt, Germany, October 2002. [58] K. Kurbel, I. Loutchko, and F. Teuteberg. FuzzyMAN: An Agent-Based Electronic Marketplace with a Multilateral Negotiation Protocol. In Lindemann et al. [62], pages 126–140. [59] K. Larson and T. Sandholm. Bargaining with limited computation: Deliberation equilibrium. Artificial Intelligence, 132(2):183–217, 2001. [60] H. Laux and F. Liermann. Grundlagen der Organisation: Die Steuerung von Entscheidungen als Grundproblem der Betriebswirtschaftslehre. Springer-Verlag, Berlin / Heidelberg / New York, 5. edition, 2003. 1st ed. 1987 / 2nd ed. 1990 / 3rd ed. 1993 / 4th ed. 1997. [61] J.-G. Lee, J.-Y. Kang, and E.-S. Lee. ICOMA: An Open Infrastructure for Agent-based Intelligent Electronic Commerce on the Internet. In ICPADS ’97: Proceedings of the 1997 International Conference on Parallel and Distributed Systems, pages 648–655. IEEE Computer Society, 1997. [62] G. Lindemann, J. Denzinger, I. J. Timm, and R. Unland, editors. Multiagent System Technologies, Second German Conference, MATES 2004, Erfurt, Germany, September 29-30, 2004, Proceedings, volume 3187 of Lecture Notes in Computer Science. Springer-Verlag, 2004. [63] C. O. LLC. Commerce One Supplier Relationship Management. http://www.commerceone.com (27.12.2004), 2004. [64] A. R. Lomuscio, M. Wooldridge, and N. R. Jennings. A Classification Scheme for Negotiation in Electronic Commerce. Group Decision and Negotiation, 12(1):31–56, 2003.

[65] M. Luck, P. McBurney, and C. Preist. A Manifesto for Agent Technology: Towards Next Generation Computing. Autonomous Agents and Multi-Agent Systems, 9(3):203– 252, 2004. [66] M. Luck, P. McBurney, O. Shehory, and S. Willmott. Agent Technology: Computing as Interaction - A Roadmap for Agent-Based Computing. Technical Report, AgentLink III, September 2005. http://www.agentlink.org/roadmap/ (19.06.2006). [67] X. Luo, N. R. Jennings, N. Shadbolt, H. fung Leung, and J. H. man Lee. A fuzzy constraint based model for bilateral, multi-issue negotiations in semi-competitive environments. Artificial Intelligence, 148(1-2):53–102, 2003. [68] J. G. March and H. A. Simon. Organizations. John Wiley & Sons, Inc., New York, 1958. [69] S. Matwin, S. Szpakowicz, Z. Koperczak, G. E. Kersten, and W. Michalowski. Negoplan: An Expert System Shell for Negotiation Support. IEEE Expert: Intelligent Systems and Their Applications, 4(4):50–62, 1989. [70] J. F. Nash. The Bargaining Problem. Econometrica, 18(2):155–162, January 1950. [71] J. F. Nash. Equilibrium Points in n-Person Games. In Proceedings of the National Academy of Sciences, volume 36, pages 48–49, USA, January 1950. [72] J. F. Nash. Non-Cooperative Games. Annals of Mathematics, 54(2):286–295, 1951. [73] D. Neumann, M. Benyoucef, S. Bassil, and J. Vachon. Applying the Montreal Taxonomy to State of the Art ENegotiation Systems. Group Decision and Negotiation, 12(4):287–310, July 2003. [74] M. J. Osborne and A. Rubinstein. A Course in Game Theory. MIT Press, Cambridge, MA, USA, 1994. [75] S. Park, E. H. Durfee, and W. P. Birmingham. Emergent Properties of a Market-based Digital Library with Strategic Agents. Autonomous Agents and Multi-Agent Systems, 3(1):33–51, 2000. [76] S. Parsons and N. R. Jennings. Negotiation through argumentation-A preliminary report. In Proceedings of the Second International Conference Multi-Agent Systems (ICMAS’96), pages 267–274, Kyoto, Japan, 1996. [77] S. Parsons, C. Sierra, and N. R. Jennings. Agents that Reason and Negotiate by Arguing. Journal of Logic and Computation, 8(3):261–292, 1998. [78] R. Peters. Elektronische Märkte: Spieltheoretische Konzeption und agentenorientierte Realisierung. Information Age Economy. Physica-Verlag, Heidelberg, 2002. [79] M. Pradella and M. Colombetti. A Formal Description of a Practical Agent for E-Commerce. In Agent-Mediated Electronic Commerce III, Current Issues in Agent-Based Electronic Commerce Systems (includes revised papers from AMEC 2000 Workshop), pages 84–95. Springer-Verlag, 2001. [80] R. J. Rabelo, L. M. Camarinha-Matos, and H. Afsarmanesh. Multi-agent-based agile scheduling. Robotics and Autonomous Systems, 27(1-2):15–28, 1999. [81] I. Rahwan, S. D. Ramchurn, N. R. Jennings, P. McBurney, S. Parsons, and L. Sonenberg. Argumentation-Based Negotiation. Knowledge Engineering Review (KER), 18(4):343–375, December 2003.



[82] V. Ram, N. V. Findler, and R. M. Malyankar. Models of and Experiments with E-Markets for Electric Utilities. International Journal of Cooperative Information Systems (IJCIS), 12(1):61–89, 2003. [83] M. Rebstock. Elektronische Unterstützung und Automatisierung von Verhandlungen. Wirtschaftsinformatik, 43(6):609–617, Dezember 2001. WI - State of the Art. [84] M. Rebstock and M. Lipp. Webservices zur Integration interaktiver elektronischer Verhandlungen in elektronische Marktplätze. Wirtschaftsinformatik, 45(3):293–306, Juni 2003. [85] M. Rebstock, P. Thun, and O. A. Tafreschi. Supporting Interactive Multi-Attribute Electronic Negotiations with ebXML. Group Decision and Negotiation, 12(4):269–286, July 2003. [86] A. Reyes-Moro, J. A. Rodr´ıguez-Aguilar, M. LópezSánchez, J. Cerquides, and D. Gutierrez-Magallanes. Embedding Decision Support in E-Sourcing Tools: Quotes, A Case Study. Group Decision and Negotiation, 12(4):347– 355, July 2003. [87] J. S. Rosenschein. Rational Interaction: Cooperation Among Intelligent Agents. PhD thesis, Computer Science Department, Stanford University, Stanford, California, USA, March 1985. [88] J. S. Rosenschein and G. Zlotkin. Rules of Encounter: Designing Conventions for Automated Negotiation among Computers. MIT Press, Boston, MA, USA, 1994. [89] S. A. Ross. The Economic Theory of Agency: The Principal’s Problem. American Economic Review, 63(2):681– 690, May 1973. Papers and Proceedings of the Eighty-fifth Annual Meeting of the American Economic Association. [90] A. Rubinstein. Modeling Bounded Rationality. MIT Press, Cambridge, MA, USA, December 1997. [91] J. Sabater, C. Sierra, S. D. Parsons, and N. R. Jennings. Using multi-context systems to engineer executable agents. In Proceedings of the 6th International Workshop on Agent Theories Architectures and Languages (ATAL-99), pages 131–148, Orlando, FL, 1999. [92] L. Samuelson. Evolutionary Games and Equilibrium Selection. MIT Press, Cambridge, MA, USA, 1998. [93] T. W. Sandholm. Agents in Electronic Commerce: Component Technologies for Automated Negotiation and Coalition Formation. Autonomous Agents and Multi-Agent Systems, 3(1):73–96, 2000. [94] T. W. Sandholm. Algorithm for optimal winner determination in combinatorial auctions. Artificial Intelligence, 135(1-2):1–54, 2002. [95] T. W. Sandholm. eMediator: A Next Generation Electronic Commerce Server. Computational Intelligence, Special issue on Agent Technology for Electronic Commerce, 18(4):656–676, 2002. [96] T. W. Sandholm and V. R. Lesser. Issues in Automated Negotiation and Electronic Commerce: Extending the Contract Net Framework. First International Conference on Multi-Agent Systems (ICMAS-95), pages 328–335, January 1995. [97] T. W. Sandholm and V. R. Lesser. Leveled Commitment Contracts and Strategic Breach. Games and Economic Behavior, 35:212–270, January 2001. Special issue on AI and Economics. (Early version in Proceedings of AAAI-96).

[98] T. W. Sandholm and S. Suri. BOB: Improved winner determination in combinatorial auctions and generalizations. Artificial Intelligence, 145(1-2):33–58, 2003. [99] T. C. Schelling. The Strategy of Conflict. Harvard University Press, Cambridge, Mass., USA, 1960. [100] M. Schoop. The Worlds of Negotiation. In M. Aakhus and M. Lind, editors, Proceedings of the 9th International Working Conference on the Language Action Perspective on Communication Modeling (LAP 2004), pages 179–196, New Brunswick, New Jersey, USA, 2-3 June 2004. [101] M. Schoop, A. Jertila, and T. List. Negoisst: A Negotiation Support System for Electronic Business-to-Business Negotiations in E-Commerce. Data and Knowledge Engineering, 47(3):371–401, 2003. [102] R. Selten. Spieltheoretische Behandlung eines Oligopolmodells mit Nachfrageträgheit. Zeitschrift für die gesamte Staatswissenschaft, 121:301–324, 667–689, 1965. [103] R. Selten. Reexamination of the Prefectness Concept for Equilibrium Points in Extensive Games. International Journal of Game Theory, 4(1):25–55, 1975. [104] S. Sen. Developing an Automated Distributed Meeting Scheduler. IEEE Expert, 12(4):41–45, July/August 1997. [105] M. J. Shaw. Electronic Commerce: Review of Critical Research Issues. Information Systems Frontiers, 1(1):95–106, 1999. [106] C. Sierra, N. R. Jennings, P. Noriega, and S. Parsons. A Framework for Argumentation-Based Negotiation. In Singh et al. [111], pages 177–192. [107] C. Sierra, N. R. Jennings, P. Noriega, and S. Parsons. A Framework for Argumentation-Based Negotiation. Lecture Notes in Computer Science (LNCS), 1365:177–189, 1998. [108] H. A. Simon. Administrative Behavior: A Study of Decision-Making Processes in Administrative Organizations. Free Press, New York, 1. edition, 1947. orig. 1945 Chicago / 2nd ed. 1965/ 3rd ed. 1976 / 4th ed. 1997. [109] H. A. Simon. Models of Man: Social and Rational. John Wiley & Sons, Inc., New York, 1957. [110] M. Sinaceur and M. A. Neale. Not All Threats are Created Equal: How Implicitness and Timing Affect the Effectiveness of Threats in Negotiations. Group Decision and Negotiation, 14(1):63–85, January 2005. [111] M. P. Singh, A. S. Rao, and M. Wooldridge, editors. Proceedings of Intelligent Agents IV, Agent Theories, Architectures, and Languages, 4th International Workshop (ATAL), July 24-26, 1997, volume 1365 of Lecture Notes in Computer Science (LNCS). Springer-Verlag, Providence, Rhode Island, USA, 1998. [112] J. M. Smith. Game Theory and the Evolution of Fighting. In On Evolution, pages 8–28, Edinburgh, 1972. Edinburgh University Press. [113] M. Ströbel and C. Weinhardt. The Montreal Taxonomy for Electronic Negotiations. Group Decision and Negotiation, 12(2):143–164, 2003. [114] A. F. Stuhlmacher and M. V. Champagne. The Impact of Time Pressure and Information on Negotiation Process and Decisions. Group Decision and Negotiation, 9(6):471– 491, November 2000.



[115] T. Suyama and M. Yokoo. Strategy/False-name Proof Protocols for Combinatorial Multi-Attribute Procurement Auction. Autonomous Agents and Multi-Agent Systems, 11(1):7–21, 2005. [116] K. P. Sycara. Resolving Adversarial Conflicts: An Approach Integrating Case-Based and Analytic Methods. PhD thesis, Georgia Institute of Technology, Atlanta, GA, June 1987. [117] K. P. Sycara. Resolving Goal Conflicts via Negotiation. In Proceedings of the Seventh National Conference on Artificial Intelligence, volume 1, pages 245–250, 1988. [118] K. P. Sycara. Argumentation: Planning Other Agents’ Plans. In Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, pages 517–523, August 1989. [119] K. P. Sycara. Problem Restructuring in Negotiation. Management Science, 37(10), October 1991. [120] N. Szirbik. A Neotiation Enabling Agent Based Infrastructure: Composition and Behavior. Information Systems Frontiers, 4(1):85–99, 2002. [121] J. E. Teich, H. Wallenius, and J. Wallenius. Multiple Issue Auction and Market Algorithms for the World Wide Web, December 1998. Interim Report IR-98-109, International Institute for Applied Systems Analysis (IIASA), Austria. [122] J. E. Teich, H. Wallenius, J. Wallenius, and A. Zaitsev. A Multiple Unit Auction Algorithm: Some Theory and a Web Implementation. Electronic Markets, 9(3):199–205, 1999. [123] J. E. Teich, H. Wallenius, J. Wallenius, and A. Zaitsev. An Internet-Based Procedure for Reverse Auctions Combining Aspects of Negotiations and Auctions. In DEXA ’00: Proceedings of the 11th International Workshop on Database and Expert Systems Applications (DEXA’00) [24], pages 1010–1014. [124] M. Tennenholtz. Tractable combinatorial auctions and bmatching. Artificial Intelligence, 140(1-2):231–243, 2002. [125] F. Teuteberg. Experimental Evaluation of a Model for Multilateral Negotiation with Fuzzy Preferences on an Agent-based Marketplace. Electronic Markets, 13(1):21– 32, 2003. [126] F. Thomé and T. Sandholm. Coalition Formation Processes with Belief Revision among Bounded-Rational Self-Interested Agents. Journal of Logic and Computation, 9(6):793–815, 1999. [127] A. Tversky and D. Kahneman. The Framing of Decisions and the Psychology of Choice. Science, 211(4481):453– 458, January 1981. [128] A. Tversky and D. Kahneman. Rational Choice and the Framing of Decisions. Journal of Business, 59(4):251– 278, October 1986. [129] H. Ulrich. Die Unternehmung als produktives und soziales System: Grundlagen der allgemeinen Unternehmungslehre, volume 1 of Schriftenreihe Unternehmung und Unternehmungsführung. Haupt Verlag, Bern, 1. edition, 1968. 2nd ed. 1970. [130] J. L. von Neumann and O. Morgenstern. Theory of Games and Economic Behavior. Princeton University Press, Princeton, New Jersey, 1. edition, 1944. 2. ed. 1947, 3. ed. 1953.

[131] R. E. Walton and R. B. McKersie. A Behavioral Theory of Labor Negotiations. McGraw-Hill, New York, 1965. [132] K.-J. Wang and C.-H. Chou. Evaluating NDF-based negotiation mechanism within an agent-based environment. Robotics and Autonomous Systems, 43(1):1–27, April 2003. [133] A. M. Wasfy and Y. A. Hosni. Two-Party Negotiation Modeling: An Integrated Fuzzy Logic Approach. Group Decision and Negotiation, 7(6):491–518, November 1998. [134] H. Weigand, M. Schoop, A. de Moor, and F. P. M. Dignum. B2B Negotiation Support: The Need for a Communication Perspective. Group Decision and Negotiation, 12(1):3–29, January 2003. [135] O. E. Williamson. The Economic Institutions of Capitalism. The Free Press, New York, 1985. [136] M. Wooldridge. An Introduction to MultiAgent Systems. John Wiley & Sons, Ltd., Chichester, UK, 2002. [137] M. Wooldridge, S. Bussmann, and M. Klosterberg. Production sequencing as negotiation. In Proceedings of the First International Conference on the Practical Application of Intelligent Agents and Multi-Agent Technology (PAAM-96), pages 709–726, London, UK, April 1996. [138] P. R. Wurman, M. P. Wellman, and W. W. E. The Michigan Internet AuctionBot: A Configurable Auction Server for Human and Software Agents. In Proceedings of the Second International Conference on Autonomous Agents, Minneapolis, MN, USA, 1998. [139] G. Yee and L. Korba. Bilateral E-Services Negotiation under Uncertainty. In SAINT ’03: Proceedings of the 2003 Symposium on Applications and the Internet, page 352. IEEE Computer Society, January 2003. [140] Y. Yuan, J. B. Rose, and N. P. Archer. A Web-Based Negotiation Support System. Electronic Markets, 8(3):13–17, 1998. [141] L. A. Zadeh. Fuzzy Sets. Journal of Information and Control, 8:338–353, 1965. [142] X. Zhang, V. R. Lesser, and S. Abdallah. Efficient Management of Multi-Linked Negotiation Based on a Formalized Model. Autonomous Agents and Multi-Agent Systems, 10(2):165–205, 2005. [143] X. Zhang, V. R. Lesser, and R. Podorozhny. MultiDimensional, MultiStep Negotiation. Autonomous Agents and Multi-Agent Systems, 10(1):5–40, 2005. [144] G. Zlotkin and J. S. Rosenschein. Negotiation and Task Sharing among Autonomous Agents in Cooperative Domains. In N. S. Sridharan, editor, Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, pages 912–917, San Mateo, CA, 1989. Morgan Kaufmann. [145] G. Zlotkin and J. S. Rosenschein. Mechanism design for automated negotiation, and its application to task oriented domains. Artificial Intelligence, 86(2):195–244, 1996.
