Probabilistic Computation and Emotion as Self-regulation

Haugwitz, Rickard von; Dodig-Crnković, Gordana

doi:10.1145/2797433.2797442

Cited by 2 publications

(1 citation statement)

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“…The info-computational framework takes the world to be information for an agent, with computation understood as the dynamics of information. This approach broadens the definition of cognition, incorporating the idea of "life = cognition" (=natural info-computation) and EEEE with both subsymbolic (data-based, signal mediated, low-level) and symbolic (high-level) information processing [21]. As a consequence, cognition in other living beings and distributed cognition of social networks have been part of the same approach.…”

Section: Morphological Computation In Robotics and General Morphological Computationmentioning

confidence: 99%

Morphological, Natural, Analog, and Other Unconventional Forms of Computing for Cognition and Intelligence

Dodig-Crnković

2020

IS4SI 2019 Summit

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According to the currently dominant view, cognitive science is a study of mind and intelligence focused on computational models of knowledge in humans. It is described in terms of symbol manipulation over formal language. This approach is connected with a variety of unsolvable problems, as pointed out by Thagard. In this paper, I argue that the main reason for the inadequacy of the traditional view of cognition is that it detaches the body of a human as the cognizing agent from the higher-level abstract knowledge generation. It neglects the dynamical aspects of cognitive processes, emotions, consciousness, and social aspects of cognition. It is also uninterested in other cognizing agents such as other living beings or intelligent machines. Contrary to the traditional computationalism in cognitive science, the morphological computation approach offers a framework that connects low-level with high-level approaches to cognition, capable of meeting challenges listed by Thagard. To establish this connection, morphological computation generalizes the idea of computation from symbol manipulation to natural/physical computation and the idea of cognition from the exclusively human capacity to the capacity of all goal-directed adaptive self-reflective systems, living organisms as well as robots. Cognition is modeled as a layered process, where at the lowest level, systems acquire data from the environment, which in combination with the already stored data in the morphology of an agent, presents the basis for further structuring and self-organization of data into information and knowledge.

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Section: Morphological Computation In Robotics and General Morphological Computationmentioning

confidence: 99%

Morphological, Natural, Analog, and Other Unconventional Forms of Computing for Cognition and Intelligence

Dodig-Crnković

2020

IS4SI 2019 Summit

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Cognition as Embodied Morphological Computation

Dodig-Crnković

2018

Studies in Applied Philosophy, Epistemology and Rational Ethics

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Cognitive science is considered to be the study of mind (consciousness and thought) and intelligence in humans. Under such definition variety of unsolved/unsolvable problems appear. This article argues for a broad understanding of cognition based on empirical results from i.a. natural sciences, selforganization, artificial intelligence and artificial life, network science and neuroscience, that apart from the high level mental activities in humans, includes subsymbolic and subconscious processes, such as emotions, recognizes cognition in other living beings as well as extended and distributed/social cognition. The new idea of cognition as complex multiscale phenomenon evolved in living organisms based on bodily structures that process information, linking cognitivists and EEEE (embodied, embedded, enactive, extended) cognition approaches with the idea of morphological computation (info-computational self-organisation) in cognizing agents, emerging in evolution through interactions of a (living/ cognizing) agent with the environment. 1 Understanding Cognition Cognitive science is currently defined as a study of processes of knowledge generation through perception, thinking (reasoning), memory, learning, problem solving, and similar. Thagard (2013) makes an extension of the idea of "thinking" to include emotional experience. This move bridges some of the distance between cognition as thinking and its (sub-)processes, but the fundamental problem of generative mechanisms that can dynamically overarch the chasm between matter and mind remains. The definition of cognitive science does not mention biology, chemistry, (quantum-nano-, etc.) physics or chaos theory, self-organisation, and artificial life, artificial intelligence or data science, extended mind, or distributed cognition as studied with help of network science, sociology or ecology. On the current view, cognition is about high-level processes remote from physicalchemical-biological substrate. It is modeled either by classical sequential computation, understood as symbol manipulation, or by neural networks. On the other hand, historically, behaviorism offered an alternative view of cognition with the focus on the observable behavior of a subject. This divide is mirrored in the present day schism between cognitivism/computationalism on one side and EEEE (embodied, embedded, enactive, extended) cognition on the other. There have been numerous attempts to bridge this gap AQ1 AQ2

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Probabilistic Computation and Emotion as Self-regulation

Cited by 2 publications

References 30 publications

Morphological, Natural, Analog, and Other Unconventional Forms of Computing for Cognition and Intelligence

Morphological, Natural, Analog, and Other Unconventional Forms of Computing for Cognition and Intelligence

Cognition as Embodied Morphological Computation

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