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Constructing the Basic Umwelt of Artificial Agents: An Information-Theoretic Approach

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Advances in Artificial Life (ECAL 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4648))

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Abstract

In the context of situated and embodied cognition, we evaluate an information-theoretic approach to the construction of the basic Umwelt of an artificial agent. We make the assumption that the construction of such a basic Umwelt is an emergent property of the coupling between the agent and its environment where the goal of the agent is to maximize its control abilities. An information-theoretic approach of the perception-action loop allows us to evaluate the capacity of the agent to inject information into its environment and to later recapture this information in its own sensors. We define a construction mechanism based on an automaton that generates internal states relevant to the agent in terms of perception-action loop. Optimizing this automaton leads to internal representations that can be a basis for the construction of the basic Umwelt of the agent. We illustrate the properties of the proposed mechanism in a simple example where an agent is acting in a box world. Simulation results show that this construction mechanism leads to a representation that captures important properties of the environment.

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Fernando Almeida e Costa Luis Mateus Rocha Ernesto Costa Inman Harvey António Coutinho

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© 2007 Springer-Verlag Berlin Heidelberg

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Capdepuy, P., Polani, D., Nehaniv, C.L. (2007). Constructing the Basic Umwelt of Artificial Agents: An Information-Theoretic Approach. In: Almeida e Costa, F., Rocha, L.M., Costa, E., Harvey, I., Coutinho, A. (eds) Advances in Artificial Life. ECAL 2007. Lecture Notes in Computer Science(), vol 4648. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74913-4_38

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  • DOI: https://doi.org/10.1007/978-3-540-74913-4_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74912-7

  • Online ISBN: 978-3-540-74913-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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