Abstract
According to the modern theory of adaption of socioeconomic systems to unknown environments only the interaction between agents can be responsible for various emergent phenomena governed by decision-making and agent learning. Previously we advocated the idea that adopting a more complex model for the agent individual behavior including rational and irrational reasons for decision-making, a more diverse spectrum of macro-level behaviors can be expected. To justify this idea we have developed a model based on the reinforcement learning paradigm extended to including an additional channel of processing information; an agent is biased by novelty seeking, the intrinsic inclination for exploration. In the present paper we demonstrate that the behavior of the single novelty-seeking agent may be extremely irregular and the concepts of chaos can be used to characterize it.
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Lubashevsky, I., Zgonnikov, A., Maslov, S., Goussein-zade, N. (2017). Complex Dynamics of Single Agent Choice Governed by Dual-Channel Multi-Mode Reinforcement Learning. In: Kavoura, A., Sakas, D., Tomaras, P. (eds) Strategic Innovative Marketing. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-33865-1_68
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DOI: https://doi.org/10.1007/978-3-319-33865-1_68
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