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2017 | OriginalPaper | Buchkapitel

Combinatorial Auction Based Mechanism Design for Course Offering Determination

verfasst von : Anton Vassiliev, Fuhua Lin, M. Ali Akber Dewan

Erschienen in: Digital Human Modeling. Applications in Health, Safety, Ergonomics, and Risk Management: Ergonomics and Design

Verlag: Springer International Publishing

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Abstract

Course Offering Determination (COD) is a strategy of an educational institution to maximize the satisfaction of the students and the enrollment of the courses within budget and other resource constraint. COD is a resource allocation problem which is difficult to solve due to the complexity in students’ preferences and resource constraints. In this paper, a mechanism for interactive and dynamic decision making is proposed to solve the problem. In this mechanism, the agents negotiate using a protocol which is based on a multi-unit Combinatorial Auctions (CA). To solve the Winner Determination Problem (WDP) in CA, we modified the Branch On Bids (BOB) algorithm to account for multi-unit nature of courses as well as the other constraints from students and administrators. A case study demonstrates the ability and effectiveness of the proposed mechanism in COD for the graduate and undergraduate level studies.

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Literatur
1.
Lin, F., Chen, W.: Designing a multiagent system for course-offering determination. In: Boella, G., Elkind, E., Savarimuthu, B.T.R., Dignum, F., Purvis, M.K. (eds.) PRIMA 2013. LNCS (LNAI), vol. 8291, pp. 165–180. Springer, Heidelberg (2013). doi:10.​1007/​978-3-642-44927-7_​12 CrossRef
2.
Schwind, M.: Combinatorial auctions for resource allocation. In: Schwind, M. (ed.) Dynamic Pricing and Automated Resource Allocation for Complex Information Services. LNEMS, vol. 589, pp. 137–190. Springer, Heidelberg (2007). doi:10.​1007/​978-3-540-68003-1_​5 CrossRef
3.
Oprea, M.: MAS-UP-UCT: a multi-agent system for university course timetable scheduling. Int. J. Comput. Commun. Control 2(1), 94–102 (2007)MathSciNetCrossRef
4.
Vassileva, J., McCalla, G., Greer, J.: Multi-agent multi-user modeling in I-Help. User Model. User-Adap. Inter. 13(1), 179–210 (2003)CrossRef
5.
Hamdi, M.S.: MASACAD: a multiagent-based approach to information customization. IEEE Intell. Syst. 21(1), 60–67 (2006)CrossRef
6.
Tariq, M., Mirza, M., Akbar, R.: Multi-agent based university time table scheduling system. Int. J. Multidiscip. Sci. Eng. 1(1), 33–39 (2010)
7.
Vainio, A., Salmenjoki, K.: Improving study planning with an agent-based system. Informatica 29, 453–459 (2005)
8.
9.
10.
Smith, R.G.: The contract net protocol: high-level communication and control in a distributed problem solver. IEEE Trans. Comput. C-29(12), 1104–1113 (1980)CrossRef
11.
Rosenschein, J.S., Zlotkin, G.: Rules of Encounter: Designing Conventions for Automated Negotiation Among Computers. MIT Press, Cambridge (1994)
12.
Ledyard, J., Olson, M., Porter, D., Swanson, J., Torma, D.: The first use of a combined-value auction for transportation services. Interfaces 32(5), 4–12 (2002)CrossRef
13.
Crampton, P., Kwerel, E., Rosston, G., Skrzypacz, A.: Using spectrum auctions to enhance competition in wireless services. J. Law Econ. 54(4), 167–188 (2011)CrossRef
14.
Porter, D., Rassenti, S., Roopnarine, A., Smith, V.: Combinatorial auction design. Natl. Acad. Sci. 100(19), 11153–11157 (2003)MathSciNetCrossRefMATH
15.
16.
Rassenti, S., Smith, V., Bulfin, R.: A combinatorial auction mechanism for airport time slot allocation. Bell J. Econ. 13(2), 402–417 (1982)CrossRef
17.
Boutilier, C., Hoos, H.: Bidding languages for combinatorial auctions. In: International Joint Conference on Artificial Intelligence, Seattle, USA, August 2001
18.
Cerquides, J., Endriss, U., Giovannucci, A., Rodriguez-Aguilar, J.: Bidding languages and winner determination for mixed multi-unit combinatorial auctions. In: International Joint Conference on Artificial Intelligence, Hyderabad, India, January 2007
19.
Lehmann, D., Müller, R., Sandholm, T.: The winner determination problem. In: Cramton, P., Shoham, Y., Steinberg, R. (eds.) Combinatorial Auctions, pp. 297–318. MIT Press, Cambridge (2006)
20.
Anderson, A., Tenhunen, M., Ygge, F.: Integer programming for combinatorial auction winner determination. In: International Conference on Multiagent Systems, Boston, MA, July 2000
21.
Rothkopf, M., Pekec, A., Harstad, R.: Computationally manageable combinatorial auctions. Manag. Sci. 44(8), 1131–1147 (1998)CrossRefMATH
22.
Sandholm, T., Suri, S.: BOB: improved winner determination in combinatorial auctions and generalizations. Artif. Intell. 145, 33–58 (2003)MathSciNetCrossRefMATH
23.
Sandholm, T., Subhash, S., Gilpin, A., Levine, D.: CABOB: a fast optimal algorithm for combinatorial auctions. In: International Joint Conference on Artificial Intelligence, Seattle, USA, August 2001
24.
Lehmann, D., O’Callagham, L., Shoham, Y.: Truth revelation in rapid, approximately efficient combinatorial auctions. J. ACM 49(5), 96–102 (2002)CrossRef
25.
Sandholm, W.: Distributed rational decision making. In: Multi-agent Systems, pp. 201–258. MIT Press, Cambridge (1999)
26.
Armstrong, A.J.: Optimizing course-offerings with MAS. Master’s Essay, Athabasca University, Athabasca, Alberta, March 2012
27.
Weiss, G.: Multiagent Systems - A Modern Approach to Distributed Artificial Intelligence. MIT Press, London (1999)
28.
Conitzer, V.: Making decisions based on the preferences of multiple agents. Commun. ACM 53(3), 84–94 (2010)MathSciNetCrossRef
29.
Stone, P., Veloso, M.: Multiagent systems: a survey from a machine learning perspective. Auton. Robot. 8(3), 345–383 (2000)CrossRef
30.
Wooldridge, M., Jennings, N.R., Kinny, D.: The gaia methodology for agent-oriented analysis and design. J. Auton. Agents Multi-agent Syst. 3(3), 285–312 (2000)CrossRef
31.
Winikoff, M., Padgham, L.: Agent-oriented software engineering. In: Multiagent Systems, pp. 695–758. MIT Press, Heidelberg (2014)
32.
Dorca, F.A., Lopes, C.R., Fernandes, M.A.: A multiagent architecture for distance education systems. In: IEEE International Conference on Advanced Learning Technologies, Athens, Greece, July 2003
33.
Graesser, A., Chipman, P., Haynes, B., Olney, A.: AutoTutor: an intelligent tutoring system with mixed-initiative dialogue. IEEE Trans. Educ. 48(4), 612–618 (2005)CrossRef
34.
Mitrovic, A., Ohlsson, S.: Evaluation of a constraint-based tutor for a database language. Int. J. Artif. Intell. 10, 238–256 (1999)
35.
Wilson, D.C., Leland, S., Godwin, K., Baxter, A., Levy, A., Smart, J., Najjar, N., Andaparambil, J.: SmartChoice: an online recommender system to support low-income families in public school choice. AI Mag. 30(2), 46–58 (2009)
36.
Lin, F., Leung, S., Wen, D., Zhang, F., Kinshuk, McGreal, R.: E-advisor: a multi-agent system for academic advising. Int. Trans. Syst. Sci. Appl. 4(2), 89–98 (2008)
37.
Cernuzzi, L., Molensini, A., Omicini, A., Zambonelli, F.: Adaptable multi-agent systems: the case of the gaia methodology. Int. J. Softw. Eng. Knowl. Eng. 21(4), 491–521 (2011)CrossRef
38.
Moraïtis, P., Petraki, E., Spanoudakis, N.I.: Engineering JADE agents with the gaia methodology. In: Carbonell, Jaime G., Siekmann, J., Kowalczyk, R., Müller, Jörg P., Tianfield, H., Unland, R. (eds.) NODe 2002. LNCS (LNAI), vol. 2592, pp. 77–91. Springer, Heidelberg (2003). doi:10.​1007/​3-540-36559-1_​8 CrossRef
39.
Wooldridge, M.: A modern approach to distributed artificial intelligence. In: Multiagent Systems, pp. 27–77. MIT Press, Cambridge (1999)
40.
Symeonidis, A., Mikas, P.: Agent Intelligence Through Data Mining. Springer, Heidelberg (2005)MATH
41.
Russel, S., Norvig, P.: Artificial Intelligence: A Modern Approach. Prentice Hall, Upper Saddle River (2010)
42.
Sturm, A., Shehory, O.: Agent-oriented software engineering: revisiting the state of the art. In: Shehory, O., Sturm, A. (eds.) Agent-Oriented Software Engineering, pp. 13–26. Springer, Heidelberg (2014). doi:10.​1007/​978-3-642-54432-3_​2
43.
Metadaten
Titel
Combinatorial Auction Based Mechanism Design for Course Offering Determination
verfasst von
Anton Vassiliev
Fuhua Lin
M. Ali Akber Dewan
Copyright-Jahr
2017
Buch
Digital Human Modeling. Applications in Health, Safety, Ergonomics, and Risk Management: Ergonomics and Design

Print ISBN: 978-3-319-58462-1

Electronic ISBN: 978-3-319-58463-8

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-58463-8_32

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