Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
APL '95 Proceedings of the international conference on Applied programming languages
Bounded rationality and adaptive agents in economic modeling
APL '95 Proceedings of the international conference on Applied programming languages
The Artificial Life Route to Artificial Intelligence: Building Embodied, Situated Agents
The Artificial Life Route to Artificial Intelligence: Building Embodied, Situated Agents
Artificial Life
A Learning Classifier Systems Bibliography
Learning Classifier Systems, From Foundations to Applications
A Roadmap to the Last Decade of Learning Classifier System Research
Learning Classifier Systems, From Foundations to Applications
A Bigger Learning Classifier Systems Bibliography
IWLCS '00 Revised Papers from the Third International Workshop on Advances in Learning Classifier Systems
Recent trends in learning classifier systems research
Advances in evolutionary computing
Applying two-stage XCS model on global overnight effect for local stock prediction
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
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Human economic decisions are characterized by a number of factors which make them difficult to model with standard mathematical tools. Decisions can be more easily described by a set of rules, and some of them may be "rules of thumb". Economic behavior is adaptive, in that people are able to adjust to a changing environment. It is argued in this paper that the classifier system framework is a suitable means of modeling human economic decisions. A case of a simple economic decision of finding an optimal price is discussed, which is later made more complex by introducing an input variable that effects the optimal price. It is shown that classifier systems can be used in both tasks, and their performance is compared to human decisions in the same set of circumstances.