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framework:automaton-theory-and-learning-systemsAutomaton Theory and Learning Systems
Ashby's 1967 foundational work on formal automata and adaptive learning; cited as key precedent for the Good Regulator theorem.
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- CyberneticsimplementsA mathematical and engineering framework for understanding goal-directed behavior in systems through feedback control mechanisms. Cybernetics formalizes how systems maintain purposive behavior and self-regulation, with applications spanning biology (morphogenetic control), behavioral science, and artificial systems; it provides rigorous language to analyze teleological processes without invoking teleology.
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Sentience criterion; capacity occurs even in gene regulatory networks and non-neural morphogenetic agents.
- Future AI that may be rational, autonomous, and possibly conscious but lack affective consciousness.
- Neural networks and physical systems with emergent collective computational abilities (Hopfield, 1982)concept0.752Original Hopfield network paper; the attractor dynamics in TEM memory retrieval are a continuous version of this.
- Mathematical and conceptual framework for modeling complex self-organizing systems; applied here to action and cognition.
- Foundational computational paradigm of local rules producing emergent global behavior, extended by this work
- Models where intelligence arises from organisation of connections between simple processing units, used as basis for evolutionary connectionism
- Extension of the Universality Hypothesis to consciousness: if consciousness solves a well-defined computational problem, different systems will discover it independently