Computational Techniques for... | Buy

Offers a critical overview on the computational techniques that are frequently used for modelling learning in economics. DLC: Economics, mathematical--Study and teaching.

Preface

vii

List of Contributors

xi

Part One: Simulating in Economics

Evolutionary Economics and Simulation

3

(42)

Witold Kwasnicki

Simulation as a Tool to Model Stochastic Processes in Complex Systems

45

(28)

Klaus G. Troitzsch

Part Two: Evolutionary Approaches

Learning by Genetic Algorithms in Economics?

73

(28)

Frank Beckenbach

Can Learning-Agent Simulations Be Used for Computer Assisted Design in Economics?

101

(22)

Tony Curzon Price

On the Emergence of Attitude towards Risk

123

(22)

Steffen Huck

Wieland Muller

Martin Strobel

Interdependencies, Nearly-decomposability and Adaptation

145

(24)

Koen Frenken

Luigi Marengo

Marco Valente

Part Three: Neural Networks and Local Interaction

Neural Networks in Economics

169

(28)

Ralf Herbrich

Max Keilbach

Thore Graepel

Peter Bollmann-Sdorra

Klaus Obermayer

Genetic Algorithms and Neural Networks: A Comparison Based on the Repeated Prisoners Dilemma

197

(24)

Robert E. Marks

Hermann Schnabl

Local Interaction as a Model of Social Interaction?

221

(22)

Dorothea K. Herreiner

Part Four: Boundedly Rational and Rational Models

Memory, Learning and the Selection of Equilibria in a Model with Non-Uniqueness

243

(18)

Emilio Barucci

A Behavioral Approach to a Strategic Market Game

261

(22)

Martin Shubik

Nicolaas J. Vriend

Bayesian Learning in Optimal Growth Models under Uncertainty

283

(22)

Sardar M. N. Islam

Part Five: Cognitive Learning Models

Modelling Bounded Rationality in Agent-based Simulations Using the Evolution of Mental Models

305

(28)

Bruce Edmonds

Cognitive Learning in Prisoner's Dilemma Situations

333

(30)

Thomas Brenner

A Cognitively Rich Methodology for Modelling Emergent Socioeconomic Phenomena

363

(24)

Scott Moss

Index

387

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