Boundedly rational versus optimization-based models of strategic thinking and learning in games

The paper is a comment on the article by R. Harstad and R. Selten and considers the tradeoff between bounded rationality and optimization models in the game-theoretic context. The author shows that in most of the models elements of opimization are still retained and that it is thus more productive to further improve the optimization-based modeling rather than to abandon them altogether in favour of bounded rationality

Comparing Loyalty Program Tiering Strategies: An investigation from the gaming industry

Loyalty programs are popular marketing strategies developed for the purpose of attracting, maintaining, and enhancing customer relationships. Due to the explosive worldwide growth of, and increased competition within, the casino industry has compelled contemporary casino marketers to rely more heavily on loyalty programs to increase guest allegiance and the frequency of repeat visits from their customers. Despite the widespread usage of loyalty programs across various gaming businesses in Las Vegas, its effectiveness has not quite been validated. The purpose of this study is to examine customers’ behavioral loyalty within the Las Vegas gaming industry and examine the effectiveness of a specific loyalty program using secondary data obtained from a Las Vegas casino hotel. Specifically, this study segmented loyalty program members to investigate the effectiveness of a casino loyalty program’s tiering strategy on members’ purchase behavior. Further, this study employed Recency-Frequency-Monetary (RFM) analysis to examine two different types of tiering strategies

Incentive and stability in the Rock-Paper-Scissors game: an experimental investigation

In a two-person Rock-Paper-Scissors (RPS) game, if we set a loss worth nothing and a tie worth 1, and the payoff of winning (the incentive a) as a variable, this game is called as generalized RPS game. The generalized RPS game is a representative mathematical model to illustrate the game dynamics, appearing widely in textbook. However, how actual motions in these games depend on the incentive has never been reported quantitatively. Using the data from 7 games with different incentives, including 84 groups of 6 subjects playing the game in 300-round, with random-pair tournaments and local information recorded, we find that, both on social and individual level, the actual motions are changing continuously with the incentive. More expressively, some representative findings are, (1) in social collective strategy transit views, the forward transition vector field is more and more centripetal as the stability of the system increasing; (2) In the individual behavior of strategy transit view, there exists a phase transformation as the stability of the systems increasing, and the phase transformation point being near the standard RPS; (3) Conditional response behaviors are structurally changing accompanied by the controlled incentive. As a whole, the best response behavior increases and the win-stay lose-shift (WSLS) behavior declines with the incentive. Further, the outcome of win, tie, and lose influence the best response behavior and WSLS behavior. Both as the best response behavior, the win-stay behavior declines with the incentive while the lose-left-shift behavior increase with the incentive. And both as the WSLS behavior, the lose-left-shift behavior increase with the incentive, but the lose-right-shift behaviors declines with the incentive. We hope to learn which one in tens of learning models can interpret the empirical observation above.Comment: 19 pages, 14 figures, Keywords: experimental economics, conditional response, best response, win-stay-lose-shift, evolutionary game theory, behavior economic

Behavioral Economics: Past, Present, Future

Behavioral economics increases the explanatory power of economics by providing it with more realistic psychological foundations. This book consists of representative recent articles in behavioral economics. This chapter is intended to provide an introduction to the approach and methods of behavioral economics, and to some of its major findings, applications, and promising new directions. It also seeks to fill some unavoidable gaps in the chapters’ coverage of topics

Group selection theories are now more sophisticated, but are they more predictive?

Human beings are unique among species in their ability to cooperate in large groups of genetically unrelated individuals, and in this book, Samuel Bowles and Herbert Gintis attempt to account for the origins of this ability. The authors specialize in the use of formal models and agent-based simulations in order to precisely specify their theories of cooperation, and they often draw on studies conducted in hunter gatherer societies and in experimental economic laboratories for evidence that they find relevant to evaluating these theories. The book is a valuable review of these anthropological and economic literatures, and a thorough showcase of the authors’ expert formal theorizing about how cooperation may have evolved. However, I often found myself disagreeing with the authors’ focus on group selection as an explanation for human cooperation, and with their views on how well the empirical findings provide support for group selectionist theories

A cognitive hierarchy theory of one-shot games: Some preliminary results

Strategic thinking, best-response, and mutual consistency (equilibrium) are three key modelling principles in noncooperative game theory. This paper relaxes mutual consistency to predict how players are likely to behave in in one-shot games before they can learn to equilibrate. We introduce a one-parameter cognitive hierarchy (CH) model to predict behavior in one-shot games, and initial conditions in repeated games. The CH approach assumes that players use k steps of reasoning with frequency f (k). Zero-step players randomize. Players using k (≥ 1) steps best respond given partially rational expectations about what players doing 0 through k - 1 steps actually choose. A simple axiom which expresses the intuition that steps of thinking are increasingly constrained by working memory, implies that f (k) has a Poisson distribution (characterized by a mean number of thinking steps τ ). The CH model converges to dominance-solvable equilibria when τ is large, predicts monotonic entry in binary entry games for τ < 1:25, and predicts effects of group size which are not predicted by Nash equilibrium. Best-fitting values of τ have an interquartile range of (.98,2.40) and a median of 1.65 across 80 experimental samples of matrix games, entry games, mixed-equilibrium games, and dominance-solvable p-beauty contests. The CH model also has economic value because subjects would have raised their earnings substantially if they had best-responded to model forecasts instead of making the choices they did