Abstract
Among the possible experiments aiming to enhance Actors (active objects) to have a behavior compatible with the requirements traditionally identified for Agents, here we discuss those integrating an evolutionary fuzzy reasoning module into Actors. The resulting framework, based on the notion of FuzzyEvoAgent, allows to realise societies of Agents evolving as a result of interactions with the environment. We propose here: 1. a formal definition of FuzzyEvoAgents; 2. an architecture in Java and 3. an application to a simple scenario in artificial life (pray and predator). The results shown in this paper confirm that the evolutionary fuzzy framework may represent an important component for ensuring the autonomy of Agents, i.e. the ability to learn from interactions with the environment.
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Cerri, S.A., Loia, V. (2001). An Evolutionary View to the Design of Soft-Computing Agents. In: Di Nola, A., Gerla, G. (eds) Lectures on Soft Computing and Fuzzy Logic. Advances in Soft Computing, vol 11. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1818-5_5
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DOI: https://doi.org/10.1007/978-3-7908-1818-5_5
Publisher Name: Physica, Heidelberg
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