Cited by 180Advanced Bandit Algorithms ResearchReinforcement Learning in RoboticsAdaptive Dynamic Programming Control

An adaptive optimal controller for discrete-time Markov environments

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Witten, Ian H.·1977·Information and Control

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Crossref · 10.1016/s0019-9958(77)90354-0

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9 of 9 references verified0 citation errors · 0 not checkable

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  • These milestones include the Backpropagation algorithm, the CMAC NN model, the Expectation Maximization algorithm, Temporal Difference learning, and the ID3 algorithm.

    “These include the Backpropagation (BP) algorithm, the Cerebellar Model Articulation Controller (CMAC) NN model [11], the Expectation Maximization (EM) algorithm [115], the to-be-referred-to as Temporal Difference (TD) learning [478], and the Iterative Dichotomiser 3 (ID3) algorithm [373].”
  • Witten developed an RL approach to solve MDPs, inspired by animal behavior and learning theories, later referred to as Temporal Difference in Sutton's work.

    “At the same time, Witten developed an RL approach to solve MDPs, inspired by animal behavior and learning theories [478], that was later referred to as Temporal Difference (TD) in Sutton's work [433,434].”

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Authors
Witten, I. H.
Affiliations
University of Essex (GB)
Corresponding author
Witten, Ian H.
Venue
Information and Control
Publisher
Elsevier BV
Published
1977-08
Volume
34
Issue
4
Pages
286-295
ISSN
0019-9958 (ISSN-L)
OpenAlex
W2054940200
Cited by
180
References
9
Citations by year
2026: 2 · 2025: 5 · 2024: 8 · 2023: 10 · 2022: 11 · 2021: 11 · 2020: 12 · 2019: 9 · 2018: 11 · 2017: 3 · 2016: 1 · 2015: 5 · 2014: 3 · 2013: 3 · 2012: 6
FWCI
1.44
Type
journal article
Language
en
Open access
Locations
Information and Control (publishedVersion)
Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Advanced Bandit Algorithms Research
  • Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Adaptive Dynamic Programming Control
Keywords
adaptive optimal control, Markov decision process, optimal control, expected reward maximization, reinforcement learning

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