Design for a brain; the origin of adaptive behavior

By W. R. Ashby. 2011

463 citations recorded by the source corpus.

1 The Problem.- 2 Dynamic Systems.- 3 The Organism as Machine.- 4 Stability.- 5 Adaptation as Stability.- 6 Parameters.- 7 The Ultrastable System.- 8 The Homeostat.- 9 Ultrastability in the Organism.- 10 The Recurrent Situation.- 11 The Fully-joined System.- 12 Temporary Independence.- 13 The System with Local Stabilities.- 14 Repetitive Stimuli and Habituation.- 15 Adaptation in Iterated and Serial Systems.- 16 Adaptation in the Multistable System.- 17 Ancillary Regulations.- 18 Amplifying Adaptation.- 19 The State-determined System.- 20 Stability.- 21 Parameters.- 22 The Effects of Constancy.- References.

Subfields: Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/8b9d2a43a3aa8f3cecbc4a7fc6ac9d36dc04ba7f

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In Mechanical Engineering

Citations in the corpus

Hierarchical Approaches (2012, background): “Ashby (1952) proposed such a gating mechanism for an agent to handle recurrent situations.”
Philosophy and the practice of Bayesian statistics (2010, unknown): “Even the unpromising-sounding procedure, “Pick a model at random and keep it until its accumulated error gets too big, then pick another model completely at random,” would qualify (and could work surprisingly well under some circumstances; cf. Ashby (1960); Foster and Young (2003)).”
Trade-offs across value-domains in ecosystem services assessment. (2014, background): “Following the instiutional framework developed by Ostrom (1998) in the context of he governance of complex systems, which also refers to the ‘Law dicators 37 (2014) 220– 228 227 of Requisite Variety’ (Ashby, 1960), we argue that the ecosystem service research needs as much variety of methods as comp”
Structure learning in action (2010, background): “…locate /bbr Review Structure learning in action Daniel A. Brauna,∗, Carsten Mehringb, Daniel M. Wolperta a Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, UK b Bernstein Center for Computational Neuroscience, Freiburg, Germany a r t i c l e i n f o”
Enactive artificial intelligence: Investigating the systemic organization of life and mind (2009, background): “This last point especially sets apart embodied AI from the explicit modeling approach adopted by many proponents of computationalist AI and links it back to some research in connectionism as well as earlier work in the cybernetics tradition such as that of Ashby (1960; 1947).”
Colloquium: Criticality and dynamical scaling in living systems (2017, background): “some internal logic. Thus, the computational power of a given device is quantied by estimating the amount and diversity of associations of inputs to outputs that it can support. As rst suggested in (Ashby, 1960; Turing, 1950) and much further developed in the context of machine learning (Crutcheld a”
Merging chrominance and luminance in early, medium, and late fusion using Convolutional Neural Networks (2015, background): “In 1952, Ashby published the book “Design for a Brain: The Origin of Adaptive 1952 Behavior” [Ashby, 1960].”
Neural mechanisms for interacting with a world full of action choices. (2010, background): “…which is increasingly abandoning classical serial architectures based on explicit representations of the environment in favor of hierarchical control systems in which the basic elements are sensorimotor feedback loops (Ashby 1965, Brooks 1991, Hendriks-Jansen 1996, Meyer 1995, Sahin et al. 2007).”