Semantic information, autonomous agency and non-equilibrium statistical physics.
TLDR
This paper defines semantic information as the syntactic information that a physical system has about its environment which is causally necessary for the system to maintain its own existence, and uses recent results in non-equilibrium statistical physics to analyse semantic information from a thermodynamic point of view.Abstract:
Shannon information theory provides various measures of so-called syntactic information, which reflect the amount of statistical correlation between systems. By contrast, the concept of ‘semantic i...read more
Citations
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Design for a Brain
TL;DR: Ashby accepts, as fact, that the nervous system behaves adaptively and assumes that it is, in its essentials, mechanistic, and examines dynamic systems from the standpoint of rigorous scientific —dominantly mathematical—logic until he has evolved a theoretical counterpart of brain functioning.
References
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Journal ArticleDOI
A mathematical theory of communication
TL;DR: This final installment of the paper considers the case where the signals or the messages or both are continuously variable, in contrast with the discrete nature assumed until now.
Book
Elements of information theory
Thomas M. Cover,Joy A. Thomas +1 more
TL;DR: The author examines the role of entropy, inequality, and randomness in the design of codes and the construction of codes in the rapidly changing environment.
Book
Theory of Games and Economic Behavior
TL;DR: Theory of games and economic behavior as mentioned in this paper is the classic work upon which modern-day game theory is based, and it has been widely used to analyze a host of real-world phenomena from arms races to optimal policy choices of presidential candidates, from vaccination policy to major league baseball salary negotiations.
MonographDOI
Causality: models, reasoning, and inference
TL;DR: The art and science of cause and effect have been studied in the social sciences for a long time as mentioned in this paper, see, e.g., the theory of inferred causation, causal diagrams and the identification of causal effects.