Abstract
A real-world labor market has complex worksite interactions between a worker and an employer. This paper investigates the behavior patterns of workers and employers with a job capacity and a job concentration empirically considering a strategic coalition in an agent-based computational labor market. Here, the strategic coalition can be formed autonomously among workers and/or among employers. For each experimental treatment, the behavior patterns of agents are varied with a job capacity and a job concentration depending on whether a coalition is allowed. Experimental results show that a strategic coalition makes workers and employers aggressive in worksite interactions against their partners.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Tesfatsion, L.: Agent-based Computational Economics: Growing Economics from the Bottom Up. Artificial Life 8, 55–82 (2002)
Tesfatsion, L.: Structure, Behavior, and Market Power in an Evolutionary Labor Market with Adaptive Search. Journal of Economic Dynamics and Control 25, 419–457 (2001)
Tesfatsion, L.: Hysteresis in an Evolutionary Labor Market with Adaptive Search. In: Chen, S.-H. (ed.) Evolutionary Computation in Economics and Finance, Physics, pp. 189–210. Springer, Heidelberg (2002)
Axelrod, R.: The Evolution of Strategies in the Iterated Prisoner’s Dilemma. In: Genetic Algorithms and Simulated Annealing, ch. 3, pp. 32–41. Morgan Kaufmann, San Francisco (1987)
Colman, A.M.: Game Theory and Experimental Games. Pergamon Press, Oxford (1982)
Darwen, P.J., Yao, X.: On Evolving Robust Strategies for Iterated Prisoner’s Dilemma. In: Yao, X. (ed.) AI-WS 1993 and 1994. LNCS, vol. 956, pp. 276–292. Springer, Heidelberg (1995)
Francisco, A.: A Computational Evolutionary Approach to Evolving Game Strategy and Cooperation. IEEE Transactions on Systems, Man and Cybernetics, Part B 32(5), 498–502 (2002)
Shehory, O., Kraus, S.: Coalition Formation among Autonomous Agents: Strategies and Complexity. In: Fifth European Workshop on Modeling Autonomous Agents in a Multi-Agent World, pp. 56–72. Springer, Heidelberg (1993)
Shehory, O., Sycara, K., Jha, S.: Multi-agent Coordination through Coalition Formation. In: Rao, A., Singh, M.P., Wooldridge, M.J. (eds.) ATAL 1997. LNCS, vol. 1365, pp. 143–154. Springer, Heidelberg (1997)
Garland, A., Alterman, R.: Autonomous Agents that Learn to Better Coordinate. Autonomous Agents and Multi-Agent Systems 8(3), 267–301 (2004)
Tate, A., Bradshaw, M., Pechoucek, M.: Knowledge Systems for Coalition Operations. IEEE Intelligent Systems 17, 14–16 (2002)
Sandholm, T.W., Lesser, V.R.: Coalitions among Computationally Bounded Agents. Artificial Intelligence 94, 99–137 (1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yang, SR., Min, JK., Cho, SB. (2004). Agent-Based Evolutionary Labor Market Model with Strategic Coalition. In: Webb, G.I., Yu, X. (eds) AI 2004: Advances in Artificial Intelligence. AI 2004. Lecture Notes in Computer Science(), vol 3339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30549-1_1
Download citation
DOI: https://doi.org/10.1007/978-3-540-30549-1_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24059-4
Online ISBN: 978-3-540-30549-1
eBook Packages: Computer ScienceComputer Science (R0)