In this paper we explore several fundamental relations between formal systems, algorithms, and dynamical systems, focussing on the roles of undecidability, universality, diagonalization, and self-reference in each of these computational frameworks. Some of these interconnections are well-known, while some are clarified in this study as a result of a fine-grained comparison between recursive formal systems, Turing machines, and Cellular Automata (CAs). In particular, we elaborate on the diagonalization argument applied to distributed computation carried out by CAs, illustrating the key elements of Gödel's proof for CAs. The comparative analysis emphasizes three factors which underlie the capacity to generate undecidable dynamics within the examined computational frameworks: (i) the program-data duality; (ii) the potential to access an infinite computational medium; and (iii) the ability to implement negation. The considered adaptations of Gödel's proof distinguish between computational universality and undecidability, and show how the diagonalization argument exploits, on several levels, the self-referential basis of undecidability.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.plrev.2018.12.003DOI Listing

Publication Analysis

Top Keywords

self-referential basis
8
undecidable dynamics
8
formal systems
8
computational frameworks
8
diagonalization argument
8
gödel's proof
8
basis undecidable
4
dynamics liar
4
liar paradox
4
paradox halting
4

Similar Publications

The brain's action-mode network.

Nat Rev Neurosci

January 2025

Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA.

The brain is always intrinsically active, using energy at high rates while cycling through global functional modes. Awake brain modes are tied to corresponding behavioural states. During goal-directed behaviour, the brain enters an action-mode of function.

View Article and Find Full Text PDF

Neural Effects of One's Own Voice on Self-Talk for Emotion Regulation.

Brain Sci

June 2024

Department of Psychiatry and Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.

Article Synopsis
  • This study explores how listening to one's own voice affects brain activity compared to listening to others' voices, particularly in the context of emotion regulation.
  • Researchers used fMRI scans on 21 healthy adults while they listened to sentences in their own and others' voices, focusing on two strategies: self-affirmation and cognitive defusion.
  • Findings indicate that brain regions related to self-processing are more engaged when using cognitive defusion with one's own voice, highlighting the unique psychological impact of hearing oneself speak.
View Article and Find Full Text PDF

Discrepancies in self-rated and observer-rated depression severity may underlie the basis for biological heterogeneity in depressive disorders and be an important predictor of outcomes and indicators to optimize intervention strategies. However, the neural mechanisms underlying this discrepancy have been understudied. This study aimed to examine the brain networks that represent the neural basis of the discrepancy between self-rated and observer-rated depression severity using resting-state functional MRI.

View Article and Find Full Text PDF

Memory for words that are drawn or sketched by the participant, rather than written, during encoding is typically superior. While this drawing benefit has been reliably demonstrated in recent years, there has yet to be an investigation of its neural basis. Here, we asked participants to either create drawings, repeatedly write, or list physical characteristics depicting each target word during encoding.

View Article and Find Full Text PDF

Why death and aging ? All memories are imperfect.

Prog Biophys Mol Biol

March 2024

Department of Life Sciences, College of Health, Medicine and Life Sciences, University of Brunel, UK. Electronic address:

Recent papers have emphasized the primary role of cellular information management in biological and evolutionary development. In this framework, intelligent cells collectively measure environmental cues to improve informational validity to support natural cellular engineering as collaborative decision-making and problem-solving in confrontation with environmental stresses. These collective actions are crucially dependent on cell-based memories as acquired patterns of response to environmental stressors.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!