Computational Model Library

LAMDA - Learning Agents for Mechanism-Design Analysis (version 1.0.0)

The simulation model LAMDA demonstrates how agent-based simulation (ABS) may provide a computational testbed for mechanism design using concepts of bounded rationality (BR). ABS can be used to systematically derive and formalize different models of BR. This allows us to identify the cognitive preconditions for behavior intended by the mechanism and thereby to derive implications for the design of mechanisms.
Based on an analysis of the requirements of the decision context, we describe a systematic way of incorporating different BR concepts into an agent learning model. The presented BR concepts as simulated by agent models cannot model human behavior in its full complexity. The simplification of complex human behavior is a useful analytical construct for the controlled analysis of a few aspects and an understanding of the potential consequences of those aspects of human behavior for mechanism design.

Download Version 1.0.0
Version Submitter First published Last modified Status
1.0.0 Iris Lorscheid Mon Aug 8 12:01:20 2016 Mon Aug 8 12:01:20 2016 Published


This website uses cookies and Google Analytics to help us track user engagement and improve our site. If you'd like to know more information about what data we collect and why, please see our data privacy policy. If you continue to use this site, you consent to our use of cookies.