Emergence in Science and Philosophy

Corradini, Antonella; O’Connor, Timothy

doi:10.4324/9780203849408

Cited by 27 publications

(6 citation statements)

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“…and m > 1 such that Thus, since the "simulation irreducibility via explanatory incompressibility" in [14,15] implies that there are conditions in which Definition 4.1 is satisfied, and viceversa, we defend that the weak emergence described in [14,15] can be understood as an informal alternative, but equivalent, to the ODE captured by Definition 4.1.…”

Section: Emergence Of Algorithmic Informationmentioning

confidence: 89%

“…Only by simulating the game it would be possible to gain sufficient irreducible information about whether or not the macrostate behavior has a property in general. One can easily demonstrate that such a "simulation irreducibility via explanatory incompressibility" in [14,15] is implied by Definition 4.1.…”

Section: Emergence Of Algorithmic Informationmentioning

confidence: 94%

“…which directly contradicts Definition 4.1 for this constant c e . That is, the ODE in Definition 4.1 implies the weak emergence in [14,15]. In the opposite direction, it is straightforward to show that the weak emergence in [14,15] implies that there are O, c e and t > t + m for which Definition 4.1 is satisfied.…”

Section: Emergence Of Algorithmic Informationmentioning

confidence: 99%

“…That is, the ODE in Definition 4.1 implies the weak emergence in [14,15]. In the opposite direction, it is straightforward to show that the weak emergence in [14,15] implies that there are O, c e and t > t + m for which Definition 4.1 is satisfied. It is claimed in [14] that the simulation irreducibility is a property that is not dependent on the current limited knowledge of the observer.…”

Section: Emergence Of Algorithmic Informationmentioning

confidence: 99%

“…In [14], a weakly emergent phenomenon is defined as the one for which the macro-level states of a system can only be derivable by simulating the very system. Later, Bedau [15] refines the notion of derivability in this definition with the notion of explanatory incompressibility. For example, in Conway's Game of Life one cannot in general decide whether or not a macrostate behavior will have a certain property from the initial configurations.…”

Section: Emergence Of Algorithmic Informationmentioning

confidence: 99%

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Emergence and Algorithmic Information Dynamics of Systems and Observers

Abrahão

Zenil

2021

Preprint

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Previous work has shown that perturbation analysis in algorithmic information dynamics can uncover generative causal processes of finite objects and quantify each of its element's information contribution to computably constructing the objects. One of the challenges for defining emergence is that the dependency on the observer's previous knowledge may cause a phenomenon to present itself as emergent for one observer at the same time that reducible for another observer. Thus, in order to quantify emergence of algorithmic information in computable generative processes, perturbation analyses may inherit such a problem of the dependency on the observer's previous formal knowledge. In this sense, by formalizing the act of observing as mutual perturbations, the emergence of algorithmic information becomes invariant, minimal, and robust to information costs and distortions, while it indeed depends on the observer. Then, we demonstrate that the unbounded increase of emergent algorithmic information implies asymptotically observer-independent emergence, which eventually overcomes any formal theory that any observer might devise. In addition, we discuss weak and strong emergence and analyze the concepts of observer-dependent emergence and asymptotically observer-independent emergence found in previous definitions and models in the literature of deterministic dynamical and computable systems.

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Section: Emergence Of Algorithmic Informationmentioning

confidence: 89%

Section: Emergence Of Algorithmic Informationmentioning

confidence: 94%

Section: Emergence Of Algorithmic Informationmentioning

confidence: 99%

Section: Emergence Of Algorithmic Informationmentioning

confidence: 99%

Section: Emergence Of Algorithmic Informationmentioning

confidence: 99%

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Emergence and Algorithmic Information Dynamics of Systems and Observers

Abrahão

Zenil

2021

Preprint

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Philosophy of psychiatry: theoretical advances and clinical implications

Stein,

Nielsen,

Hartford

et al. 2024

World Psychiatry

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Work at the intersection of philosophy and psychiatry has an extensive and influential history, and has received increased attention recently, with the emergence of professional associations and a growing literature. In this paper, we review key advances in work on philosophy and psychiatry, and their related clinical implications. First, in understanding and categorizing mental disorder, both naturalist and normativist considerations are now viewed as important – psychiatric constructs necessitate a consideration of both facts and values. At a conceptual level, this integrative view encourages moving away from strict scientism to soft naturalism, while in clinical practice this facilitates both evidence‐based and values‐based mental health care. Second, in considering the nature of psychiatric science, there is now increasing emphasis on a pluralist approach, including ontological, explanatory and value pluralism. Conceptually, a pluralist approach acknowledges the multi‐level causal interactions that give rise to psychopathology, while clinically it emphasizes the importance of a broad range of “difference‐makers”, as well as a consideration of “lived experience” in both research and practice. Third, in considering a range of questions about the brain‐mind, and how both somatic and psychic factors contribute to the development and maintenance of mental disorders, conceptual and empirical work on embodied cognition provides an increasingly valuable approach. Viewing the brain‐mind as embodied, embedded and enactive offers a conceptual approach to the mind‐body problem that facilitates the clinical integration of advances in both cognitive‐affective neuroscience and phenomenological psychopathology.

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The Organization and Improvement of Behavior

Palm

2022

Neural Assemblies

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Emergence in Science and Philosophy

Cited by 27 publications

References 1 publication

Emergence and Algorithmic Information Dynamics of Systems and Observers

Emergence and Algorithmic Information Dynamics of Systems and Observers

Philosophy of psychiatry: theoretical advances and clinical implications

The Organization and Improvement of Behavior

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