scholarly journals M Equilibrium: A Theory of Beliefs and Choices in Games

2021 ◽  
Vol 111 (12) ◽  
pp. 4002-4045
Author(s):  
Jacob K. Goeree ◽  
Philippos Louis
Keyword(s):  
Game Theory ◽  
Pure Strategy ◽  
Solution Concept ◽  
Behavioral Game Theory ◽  
Coordination Problems ◽  
Behavioral Game ◽  
Empirical Regularities ◽  
Experimental Games ◽  
Series Of Experiments ◽  
Strategy Nash Equilibrium

We introduce a set-valued solution concept, M equilibrium, to capture empirical regularities from over half a century of game theory experiments. We show M equilibrium serves as a meta theory for various models that hitherto were considered unrelated. M equilibrium is empirically robust and, despite being set-valued, falsifiable. Results from a series of experiments that compare M equilibrium to leading behavioral game theory models demonstrate its virtues in predicting observed choices and stated beliefs. Data from experimental games with a unique pure-strategy Nash equilibrium and multiple M equilibria exhibit coordination problems that could not be anticipated through the lens of existing models. (JEL C72, C90, D83)

A Multidisciplinary Framework to Model Complex Team-Based Product Development

2015 ◽  
Author(s):  
Shun Takai
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Product Development ◽  
Decision Analysis ◽  
Equilibrium Analysis ◽  
Design Decision ◽  
Behavioral Game Theory ◽  
Model Complex ◽  
Behavioral Game ◽  
Team Project

This paper investigates a multidisciplinary framework that simulates design decisions in a complex team-based product development in which engineers simultaneously work in a team project and individual projects. The proposed framework integrates cooperative and noncooperative design models with (1) equilibrium analysis, (2) uncertainty modeling based on behavioral game-theory results, and (3) decision-making using decision analysis. In the proposed framework, noncooperative design is used to simulate engineers’ decisions about team project commitment and to analyze potential free-riding; cooperative design is used to model design outcomes when engineers collaborate in the team project; equilibrium analysis and behavioral game-theory results are used to infer about other engineers’ decisions; and decision analysis is used to calculate expected values of decision alternatives. The proposed framework and the design decision-making model are illustrated using a pressure vessel design as a team project conducted by two engineers: a design engineer and a materials engineer.

scholarly journals Progress in Behavioral Game Theory

1997 ◽  
Vol 11 (4) ◽  
pp. 167-188 ◽  
Author(s):  
Colin F Camerer
Keyword(s):  
Game Theory ◽  
Social Values ◽  
Future Research ◽  
Backward Induction ◽  
Behavioral Game Theory ◽  
Dominated Strategies ◽  
Behavioral Game ◽  
Experimental Findings

Behavioral game theory aims to predict how people actually behave by incorporating psychological elements and learning into game theory. With this goal in mind, experimental findings can be organized into three categories: players have systematic 'reciprocated social values,' like desires for fairness and revenge. Phenomena discovered in studies of individual judgments and choices, like 'framing' and overconfidence, are also evident in games. Strategic principles, like irrelevance of strategy labels and timing of moves, iterated elimination of dominated strategies, and backward induction, are violated. Future research should incorporate these findings, along with learning and 'pregame theory,' into formal game theory.

Depth of Reasoning and Information Revelation: An Experiment on the Distribution of k-Levels

2017 ◽  
Vol 19 (04) ◽  
pp. 1750021 ◽  
Author(s):  
Volker Benndorf ◽  
Dorothea Kübler ◽  
Hans-Theo Normann
Keyword(s):  
Game Theory ◽  
Labor Market ◽  
Empirical Distribution ◽  
Similar Distribution ◽  
Information Revelation ◽  
Behavioral Game Theory ◽  
Future Studies ◽  
Text Types ◽  
Behavioral Game ◽  
Text Model

The level-[Formula: see text] model is a workhorse in behavioral game theory. For comparisons across experiments and predictions in future studies, it is crucial to assess the empirical distribution of [Formula: see text]-levels. We present a revelation game suitable for this purpose. In a labor market context, workers can choose to reveal their productivity at a cost, and players’ strategies reveal their level of reasoning in terms of a [Formula: see text]-level. We find that the most frequently observed reasoning levels are [Formula: see text] and [Formula: see text]. In our game roughly 30% of the players are [Formula: see text] and 25% are [Formula: see text]. We compare our results to other experiments that identify level-[Formula: see text] distribution, foremost to the money request (or 11–20) game. Despite various differences to the 11–20 game, our revelation game suggests a very similar distribution of level-[Formula: see text] types.

An Application of Behavioral Game Theory in Equilibrium Analysis of Concurrent Product-Development Projects

2014 ◽  
Author(s):  
Shun Takai
Keyword(s):  
Game Theory ◽  
Product Development ◽  
Material Selection ◽  
Development Project ◽  
Equilibrium Analysis ◽  
Process Selection ◽  
Behavioral Game Theory ◽  
Dominant Design ◽  
Behavioral Game ◽  
Development Tasks

This paper analyzes design equilibrium in a concurrent product-development project using the results from behavioral game theory. In this study, a project consists of a team of three engineers who represent three product-development stages: product design, material selection, and process selection. Product-development tasks are globally distributed, and engineers are allowed to independently make product-development decisions (i.e., non-cooperative design). In addition, the engineers are evaluated according to the outcomes of both individual and team product-development tasks. When multiple design equilibria exist, but a dominant design equilibrium does not, the past behavioral-game-theory studies indicate that design equilibrium may be reached under two conditions. In the first condition, one engineer is allowed to announce his/her intended alternative even though he/she does not need to actually choose the announced alternative. In the second condition, one engineer is selected to make his/her choice first but the other engineers do not know what that choice is. Sensitivity analysis indicates that a wide variety of design equilibria will emerge depending on how engineers are evaluated.

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