Optimal Algorithms for 2 x nAB Games--A Graph-Partition Approach

[[abstract]]This paper presents new and systematic methodologies to analyze deductive games and obtain optimal algorithms for 2 ? n AB games, where n ? 2. We have invented a graphic model to represent the game-guessing process. With this novel approach, we find some symmetric and recursive structures in the process. This not only reduces the size of the search space, but also helps us to derive the optimum strategies more efficiently. By using this technique, we develop optimal strategies for 2 ? n AB games in the expected and worst cases, and are able to derive the following new results: (1) ?n/2? + 1 guesses are necessary and sufficient for 2 ? n AB games in the worst case, (2) the minimum number of guesses required for 2 ? n AB games in the expected case is (4n3 + 21n2 - 76n + 72)/12n(n - 1) if n is even, and (4n3 + 21n2 - 82n + 105)/12n(n - 1) if n is odd. The optimization of this problem bears resemblance with other computational problems, such as circuit testing, differential cryptanalysis, on-line models with equivalent queries, and additive search problems. Any conclusion of this kind of deductive game may be applied, although probably not directly, to any of these problems, as well as to any other combinatorial optimization problem.

A simple questionnaire can change everything: Are strategy choices in coordination games stable?

This paper presents results from an experiment designed to study the effect of self reporting risk preferences on strategy choices made in a subsequently played 2x2 coordination game. The main finding is that the act of answering a questionnaire about one's own risk preferences significantly alters strategic behavior. Within a best response correspondence framework, this result can be explained by a change in either risk preferences or beliefs. We find that self reporting risk preferences induces an increase in subjects' risk aversion while keeping their beliefs unchanged. Our findings raise some questions about the stability of strategy choices in coordination games. --coordination game,questionnaire,risk preferences,beliefs,best response correspondence

Agent-Based Models and Human Subject Experiments

This paper considers the relationship between agent-based modeling and economic decision-making experiments with human subjects. Both approaches exploit controlled ``laboratory'' conditions as a means of isolating the sources of aggregate phenomena. Research findings from laboratory studies of human subject behavior have inspired studies using artificial agents in ``computational laboratories'' and vice versa. In certain cases, both methods have been used to examine the same phenomenon. The focus of this paper is on the empirical validity of agent-based modeling approaches in terms of explaining data from human subject experiments. We also point out synergies between the two methodologies that have been exploited as well as promising new possibilities.agent-based models, human subject experiments, zero- intelligence agents, learning, evolutionary algorithms

When and Why? A Critical Survey on Coordination Failure in the Laboratory

Coordination games with Pareto-ranked equilibria have attracted major theoretical attention over the past two decades. Two early path-breaking sets of experimental studies were widely interpreted as suggesting that coordination failure is a common phenomenon in the laboratory. We identify the major determinants that seem to affect the incidence, and/or emergence, of coordination failure in the lab and review critically the existing experimental studies on coordination games with Pareto-ranked equilibria since that early evidence emerged. We conclude that there are many ways to engineer coordination successes.coordination games, Pareto-ranked equilibria, payoff-asymmetric equilibria, staghunt games, optimization incentives, robustness, coordination, coordination failure