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Intelligent Systems Many Manners of Adapting to Environment

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Multiple Systems (AIRSNC 2023)

Part of the book series: Contributions to Management Science ((MANAGEMENT SC.))

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Abstract

What is intelligence is a debated and still open issue. Psychologists have identified many different skills involved in intelligence, but there is no agreement on a general definition. Without entering in the debate, we will here adopt a definition pertaining to philosophical area, general enough to include most meanings currently used in psychology and in common sense and specific enough to distinguish intelligence from other capacities. Intelligence is the ability to find adaptative responses to perturbations both of the internal and the external environment recovering proper equilibrium. Most systems, artificial and natural, are intelligent in the sense of the proposed definition, as most of them have the capacity to restore their systemic balance in response to change occurring in both inner and outer milieu. We shall then investigate by which means different systems adapt to their environment and if—and in what aspects—human intelligence differs from every other kind of intelligence known to us. To answer both questions, we will distinguish objective—or intrinsic, or tacit—intelligence from subjective—or explicit—intelligence, characterized by mental activity, language, and auto conscience. We will finally support the thesis that in human being intelligence emerges thanks to the interplay among three actors: objective intelligence, subjective intelligence, and their environment(s).

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Notes

  1. 1.

    Noesis is the basic level of knowledge, consisting in the immediate apprehension of things. This level ensures direct contact with the domain of ideas and of reality. The second level, called dianoia, is the realm of judgment, where the unity of noesis is splitted to form propositions and logical inferences.

  2. 2.

    Epigenetics is the study of how behaviors and environment can cause changes that affect the way genes work.

  3. 3.

    The use of the term ‘learn’ referred to digital machines is obviously metaphorical: Humans are said to learn because they are connected to their environment, both physical and cultural, while digital machines are said to ‘learn’ when thanks to their algorithm they select all the variables they have been exposed to during their training and find the best combination of these variables to solve a problem without being explicitly programmed.

  4. 4.

    Aristotle in Prior Analytics uses the sintagm ‘apagoghé’ to refer to the syllogism whose conclusions are ‘believable’, though not formally necessary.

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Correspondence to Lucia Urbani Ulivi .

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Ulivi, L.U., Fisogni, P. (2024). Intelligent Systems Many Manners of Adapting to Environment. In: Minati, G., Pietronilla Penna, M. (eds) Multiple Systems. AIRSNC 2023. Contributions to Management Science. Springer, Cham. https://doi.org/10.1007/978-3-031-44685-6_6

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