Adaptive and evolutive algorithms: A natural logic for artificial mind

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Abstract

This paper focuses on one of the biggest challenges we face: the possibility of reproducing in an artificial agent (based on formal algorithms) some typically human capacities (based on natural logic algorithms) such as consciousness, the ability to deliberate and make moral judgments. Recent evidences arising from dynamic systems theory and statistical learning, from the psychobiology of development and molecular neuroscience are overcoming some of the fundamental assumptions of artificial intelligence and the cognitive science of the last 50 years. From the molecular level to the social one, these new approaches analyze and exploit the structure of complex causal systems physically incorporated and integrated with the environment, setting the stage for the emergence of organisms capable of adaptive flexibility and intelligent behavior.

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Maldonato, M., & Dell’Orco, S. (2016). Adaptive and evolutive algorithms: A natural logic for artificial mind. In Intelligent Systems Reference Library (Vol. 106, pp. 13–21). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-319-31053-4_3

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