Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Artificial economic life: a simple model of a stockmarket
Proceedings of the NATO advanced research workshop and EGS topical workshop on Chaotic advection, tracer dynamics and turbulent dispersion
Hidden order: how adaptation builds complexity
Hidden order: how adaptation builds complexity
Trading on the Edge: Neural, Genetic, and Fuzzy Systems for Chaotic Financial Markets
Trading on the Edge: Neural, Genetic, and Fuzzy Systems for Chaotic Financial Markets
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Financial Markets can be at Sub-Optimal Equilibria
Computational Economics - Special issue: Evolutionary processes in economics
Knowledge Growth in an Artificial Animal
Proceedings of the 1st International Conference on Genetic Algorithms
A Critical Review of Classifier Systems
Proceedings of the 3rd International Conference on Genetic Algorithms
The use of artificially intelligent agents with bounded rationality in the study of economic markets
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
A Bigger Learning Classifier Systems Bibliography
IWLCS '00 Revised Papers from the Third International Workshop on Advances in Learning Classifier Systems
Strength and Money: An LCS Approach to Increasing Returns
IWLCS '00 Revised Papers from the Third International Workshop on Advances in Learning Classifier Systems
Explorations in LCS Models of Stock Trading
IWLCS '01 Revised Papers from the 4th International Workshop on Advances in Learning Classifier Systems
ICOSSSE '09 Proceedings of the 8th WSEAS international conference on System science and simulation in engineering
Learning and predicting financial time series by combining natural computation and agent simulation
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part II
A classification framework of adaptation in multi-agent systems
CIA'06 Proceedings of the 10th international conference on Cooperative Information Agents
A comparative study of a financial agent based simulator across learning scenarios
ADMI'11 Proceedings of the 7th international conference on Agents and Data Mining Interaction
Learning predictive models for financial time series by using agent based simulations
Transactions on Compuational Collective Intelligence VI
Biased trader model and analysis of financial market dynamics
International Journal of Knowledge-based and Intelligent Engineering Systems
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In this paper we describe a simple model of adaptive agents of different types, represented by Learning Classifier Systems (LCS), which make investment decisions about a risk free bond and a risky asset under a well defined stock market environment. Our main aim is to explore the degree of reliability that artificially intelligent agents can have when applied to real life economic problems. We do this by evaluating whether an LCS is able to represent competent traders in a real market scenario in which daily stock prices and dividends are given to the agents exogenously, so permitting us to focus on the dynamics and evolution of the behaviour of these evolving traders without having to be concerned about how their actions affect the market. We present results of adaptive and non-adaptive simulations over a period of ten years of real data of a specific stock and show that the artificial agents, by displaying different and rich behaviours evolved throughout the simulations, are able to discover and refine novel and successful sets of market strategies that can outperform baseline strategies such as buy-and-hold or merely keeping money in the bank at a good rate of interest, even though the agents pay commission on every trade.