The Institute for Mathematical Behavioral Sciences in the School of Social Sciences at the University of California, Irvine (UCI), created in 1992, is the successor to the Irvine Research Unit in Mathematical Behavioral Sciences that was formed in 1988. It is a specialized research center to facilitate interaction and common research goals among scientists whose purpose is to formulate precisely and test theories of human behavior.
The Institute was created to augment existing, interdisciplinary strengths at UCI in mathematical applications to the behavioral sciences and to foster the highest quality research in the application of mathematical models to better understand human behavior, both individual and social.
Faculty associated with the Institute span the following areas: anthropology, cognitive science, economics, engineering, geography, mathematics, political science, and sociology. Additional faculty affiliated with the Institute come both from these and other disciplines, including philosophy, mathematics, management science, and psychobiology.
Investigating the interactions between universal and culturally specific influences on color categorization across individuals and cultures has proven to be a challenge for human color categorization and naming research. The present article simulates the evolution of color lexicons to evaluate the role of two realistic constraints found in the human phenomenon: (i) heterogeneous observer populations and (ii) heterogeneous color stimuli. Such constraints, idealized and implemented as agent categorization and communication games, produce interesting and unexpected consequences for stable categorization solutions evolved and shared by agent populations. We find that the presence of a small fraction of color deficient agents in a population, or the presence of a "region of increased salience" in the color stimulus space, break rotational symmetry in population categorization solutions, and confine color category boundaries to a subset of available locations. Further, these heterogeneities, each in a different, predictable, way, might lead to a change of category number and size. In addition, the concurrent presence of both types of heterogeneity gives rise to novel constrained solutions which optimize the success rate of categorization and communication games. Implications of these agent-based results for psychological theories of color categorization and the evolution of color naming systems in human societies are discussed.
We compare replicator dynamics for some simple games with and without the addition of conformist bias. The addition of conformist bias can create equilibria, it can change the stability properties of existing equilibria, it may leave the equilibrium structure intact but change the relative size of basins of attraction, or it may do nothing at ali. Examples of each ofthe foregoing are given.
Trust and trustworthiness are crucial to the survival of online markets, and reputation systems that rely on feedback from traders help sustain trust. However, in current online auction markets only half of the buyers leave feedback after ransactions, and nearly all of it is positive. In this paper, I propose a mechanism whereby sellers can provide rebates to buyers contingent on buyers provision of reports. Using a game theoretical model, I show how the rebate incentive mechanism can increase reporting. In both a pure adverse selection model, and a model with adverse selection and moral hazard, there exists a pooling equilibrium where both good and bad sellers choose the rebate option, even though their true types are revealed through feedback. In the presence of moral hazard, the mechanism induces bad sellers to improve the quality of the contract.