Abstract
The paper uses ideas from Machine Learning, Artificial Intelligence and Genetic Algorithms to provide a model of the development of a ‘fight-or-flight’ response in a simulated agent. The modelled development process involves (simulated) processes of evolution, learning and representation development. The main value of the model is that it provides an illustration of how simple learning processes may lead to the formation of structures which can be given a representational interpretation. It also shows how these may form the infrastructure for closely-coupled agent/environment interaction.
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Thornton, C. Brave Mobots Use Representation: Emergence of Representation in Fight-or-Flight Learning. Minds and Machines 7, 475–494 (1997). https://doi.org/10.1023/A:1008206631439
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DOI: https://doi.org/10.1023/A:1008206631439