A Behavioral Approach to Learning in Economics - Towards an Economic Theory of Contingent Learning

In economics, adjustment of behavior has traditionally been treated as a "black box." Recent approaches that focus on learning behavior try to model, test, and simulate specific adjustment mechanisms in specific environments (mostly in games). Results often critically depend on distinctive assumptions, and are not easy to generalize. This paper proposes a different approach that aims to allow for more general conclusions in a methodologically more compatible way. It is argued that the introduction of the main determinants of learning behavior as situational restrictions into the standard economic model may be a fruitful way to capture some important aspects of human behavior that have often been omitted in economic theory. Based on a simple model of learning behavior (learning loop), robust findings from psychology are used to explain behavior adjustment, and to identify its determinants (contingent learning). An integrative methodology is proposed where the "black box" is not opened, but instead the factors that determine what happens inside, and the limits imposed by theses factors can be analyzed and used for model building. The paper concludes with testable hypotheses about learning behavior in the context of economics.microeconomics, game theory, learning theory, experiments

Civilization and the evolution of short sighted agents

We model an assurance game played within a population with two types of individuals -- short-sighted and foresighted. Foresighted people have a lower discount rate than short sighted people. These phenotypes interact with each other. We define the persistent interaction of foresighted people with other foresighted people as a critical element of civilization while the interaction of short sighted people with other short sighted people as critical to the failure of civilization. We show that whether the short sighted phenotype will be an evolutionary stable strategy (and thus lead to the collapse of civilization) depends on the initial proportion of short sighted people relative to people with foresight as well as their relative discount rates. Further we explore some comparative static results that connect the probability of the game continuing and the relative size of the two discount rates to the likelihood that civilization will collapse.society; breakdown; evolution; replicator; dynamic; process; civilization; conflict; institution

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

An Investigation Report on Auction Mechanism Design

Auctions are markets with strict regulations governing the information available to traders in the market and the possible actions they can take. Since well designed auctions achieve desirable economic outcomes, they have been widely used in solving real-world optimization problems, and in structuring stock or futures exchanges. Auctions also provide a very valuable testing-ground for economic theory, and they play an important role in computer-based control systems. Auction mechanism design aims to manipulate the rules of an auction in order to achieve specific goals. Economists traditionally use mathematical methods, mainly game theory, to analyze auctions and design new auction forms. However, due to the high complexity of auctions, the mathematical models are typically simplified to obtain results, and this makes it difficult to apply results derived from such models to market environments in the real world. As a result, researchers are turning to empirical approaches. This report aims to survey the theoretical and empirical approaches to designing auction mechanisms and trading strategies with more weights on empirical ones, and build the foundation for further research in the field

Learning in sender-receiver games

game theory;learning;testing

Distributed control based on evolutionary game theory: multi-agent experiment

In this Master's thesis are applied distributed consensus and game theoretical algorithms to control a population of agents. The agents are embodies by Lego Mindstorm robots and controlled remotely with Bluetooth by the PC. Using a platform implemented in LabVIEW, which includes a camera and a pattern recognition tool, the robots are controlled to perform different tasks such as convergence to consensus position and formatio