Abstract
This article examines the group processes studied in oligopoly theory and in decentralized artificial intelligence. We develop a unifying perspective for the research on the behavior of autonomous interacting agents. Among the many questions of interest in these disciplines are the ways of creating and reaching cooperation by a group of self-interested independent decentralized agents. In this respect, the models and results of oligopoly theory can also be used both in decentralized artificial intelligence and in many other areas of research, such as group decision making, negotiation support, and organizational theory. In particular, the important idea of reshaping goals with strategic information sharing and transmission—incentive communication—has received little attention outside the field of economics. On the other hand, oligopoly theory and experimental economics can especially benefit from the computational methods and tools of artificial intelligence and modern decision support technology. To demonstrate this we have built a prototype of an experimental market analysis environment. Its potential in the analysis of group processes is illustrated with examples.
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Verkama, M., Hämäläinen, R.P. & Ehtamo, H. Multi-agent interaction processes: From oligopoly theory to decentralized artificial intelligence. Group Decision and Negotiation 1, 137–159 (1992). https://doi.org/10.1007/BF00406752
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DOI: https://doi.org/10.1007/BF00406752