Asymptotic Stability in the Lovász-Shapley Replicator
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*Manuscript Asymptotic Stability in the Lov´asz-Shapley Replicator Dynamic for Cooperative Games∗ Andr´eCasajusy Michael Krammz Harald Wiesex November 20, 2019 Abstract We derive population dynamics from finite cooperative games with trans- ferable utility, where the players are interpreted as types of individuals. We show that any asymptotically stable population profile is characterized by a coalition: while the types in the coalition have the same positive share, the other types vanish. The average productivity of such a stable coalition must be greater than the average productivity of any proper sub- or super- coalition. In simple monotonic games, this means that exactly the minimal winning coalitions are stable. Possible applications are the analysis of the organizational structure of businesses or the population constitution of eu- social species. ∗We would like to thank Markus Kunze, Pierfrancesco La Mura, Wolfgang Leininger, Lars Metzger, Heinrich Nax, Karl Friedrich Siburg, William Thomson, and J¨orgenWeibull for valu- able comments. This paper also benefited from discussions and remarks at the European Meeting on Game Theory 2015 (SING, St. Petersburg), the 2nd Workshop on Economics and Biology (Toulouse), and the 3rd Workshop on Cooperative Game Theory in Business Practice (Leipzig). We are grateful for the comments of two anonymous referees and an associate editor. Andr´e Casajus: Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Founda- tion) - 388390901. yHHL Leipzig Graduate School of Management, Germany and Dr. Hops Craft Beer Bar, Germany, Email: [email protected] zCorresponding author, Technical University of Dortmund, Vogelpothsweg 87, 44221 Dort- mund, Germany, Email: [email protected] xUniversity of Leipzig, Email: [email protected] Keywords: cooperative game theory, evolutionary game theory, replicator dy- namics, asymptotic stability, Lov´asz-Shapleyvalue, simple monotonic games JEL codes: C71, C73 2 1 Introduction For a long time, non-cooperative game theory has employed the evolution- ary approach to model the behavior of boundedly rational agents and to analyze the relation between the stable outcomes of the dynamical process generated by their repeated interaction and the common static solution concept of Nash equilibrium (see, e.g., Mailath, 1998 or Samuelson, 2002 for discussions). In contrast to non-cooperative game theory, cooperative game theory shifts the focus from modeling strategic interactions and the agents' strategic reasoning to payoffs: it asks questions about which pay- off distribution among the players of a given cooperative game can, for instance, be considered as fair or stable (see, e.g., McLean, 2015). The non-cooperative concept of the Nash equilibrium has taken a cen- tral role in the study of game theory in a rather literary sense. On the one hand, the idea of the Nash program, starting with Nash (1953), is to pro- vide non-cooperative foundations for cooperative solution concepts based on the Nash equilibrium. On the other hand, as mentioned above, Smith and Price (1973) and many other researchers started to think about evolu- tionary foundations of the Nash equilibrium about two decades later. Our modeling approach skips the Nash equilibrium in the chain of reasoning and directly connects cooperative and evolutionary game theory. We in- troduce the evolutionary methodology to cooperative game theory in order to answer questions on the relation between the properties of the underly- ing cooperative game and the stable outcomes of a dynamical evolutionary process. In non-cooperative game theory, evolutionary pressures work against strategies, for instance, dominated strategies may die out (see, e.g., Hof- bauer and Weibull, 1996). In our setup, evolution takes place over types of individuals and not over strategies. In this way, pressures work against 1 certain coalitions, for example, non-minimal winning coalitions (see Corol- lary 2). We can thus analyze the relation between asymptotically stable population profiles and the underlying transferable utility (TU) game. The interpretation of the evolutionary dynamics in our model is il- lustrated with an economic example in Section 2 and can be outlined as follows. We consider a society that consists of infinitely many individuals of finitely many different types. The types correspond to the players of a cooperative game. They are (economic) entities characterized by distinct productive capabilities, such as specific business departments in an organi- zation or specific casts of a eusocial species1. The individuals, e.g., members of a specific business department or cast, are programed to perform cer- tain tasks according to their type and contribute to the organization's or the society's total reproductive success or fitness, i.e., its growth in time. This is modelled by the Lov´aszextension of a finite TU game (see Lov´asz, 1983 and Algaba et al., 2004), which embodies a particular Leontief-type technology for the production of fitness. Eventually, the total fitness has to be distributed among the different types. This is modelled by the Lov´asz- Shapley value (see Casajus and Wiese, 2016) that rewards only the scarce types, which is in line with the Leontief-type technology. Given this dis- tribution, the composition of the society evolves in time according to the replicator dynamic, which is the most commonly used imitative dynamic in the literature (see Sandholm, 2010, Section 5.3) and which is most suitable to capture the idea of individuals reproducing according to their fitness 1A common \criterion for eusociality is the presence of castes, which are groups of individuals that become irreversibly behaviorally distinct at some point prior to repro- ductive maturity. Eusocial societies are characterized by two traits: (1) helping by individuals of the less-reproductive caste, and (2) either behavioral totipotency of only the more reproductive caste (facultative eusociality) or totipotency of neither caste (ob- ligate eusociality)" (Crespi and Yanega, 1995, p. 109). Examples are the European hornet (Vespa crabro) or the naked mole rat (Heterocephalus glaber). 2 derived from the cooperative game. Now, one can study the prolifera- tion of the types and, in particular, stable compositions of the society for the resulting replicator dynamic under the Filippov solution (see Filippov, 1988). To our knowledge, we are the first to derive an evolutionary dynamic from a cooperative game in a similar fashion as it is done in non-cooperative evolutionary game theory without incorporating non-cooperative aspects. This cooperative approach has particular appeal when types represent orga- nizational departments of a collaborative enterprise, such as a large business corporation, or casts of a eusocial species. Usually, it is considered that \[o]n general grounds of methodological individualism, noncooperative games are prior to cooperative games" (see Elster, 1982, p. 466). We do not contest this conventional approach of economic theory (or its value) to analyze aggregate phenomena by exam- ining the actions and incentives of individual entities. Rather, our aim is to provide a complementary view on the \links between aggregate analy- sis and the study of individual behavior" (see Elster, 1982, p. 477). Some researchers have pushed forward that methodological individualism alone cannot explain all aspects of socio-economic interactions and thus that so- cial context and institutions need to be included in the analysis (see New- ton, 2019 and Hodgson, 2007). Furthermore, the debate on the evolution of eusociality2 emphasizes that it might be insightful to provide theories 2The evolution of eusociality is debated controversially among evolutionary biologists. It has challenged the predominant idea of the inclusive fitness theory (in this case, kin selection; see, e.g., Hamilton, 1964), which postulates that evolution takes place at the level of individuals and thus is loosely related to the non-cooperative approach in game theory. In contrast, some researchers advance the idea of group selection to explain eusociality (see Wilson and H¨olldobler,2005 and Nowak et al., 2010), which is an approach similar to cooperative game theory, since it assumes that evolution takes place at the level of groups. In view of this debate, skipping the non-cooperative approach of 3 v(f1g) = 3 v(f1; 2g) = 4 v(N) = 8 v(f2g) = 2 v(f1; 3g) = 5 v(;) = 0 v(f3g) = 1 v(f2; 3g) = 7 Table 1: A three-player cooperative game with transferable utility which take the opposite route, assuming that individual behavior (at least partly) emerges from the properties of a business department, or, in the biological context, of a cast. Our approach adds evolutionary pressures to this perspective, which gives an alternative foundation of the emergence of group properties, such as an evolutionary stable constitution of business units in an entrepreneurial organization. Our goal is to characterize evolutionary stable population profiles in a setting in which the evolutionary process is determined by an underlying transferable utility game. Consider, for instance, the cooperative game with the player set N = f1; 2; 3g defined by the coalition function v as in Table 1, which determines the worth generated by any specific coalition. We derive a simple criterion to characterize stable population profiles even in games as asymmetric and rather complex as the one defined in Table 1. Our results imply that the profiles corresponding to the coalitions f1g and f2; 3g are evolutionary