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Embedding a grammatical description in deterministic chaos: an experiment in recurrent neural learning

https://doi.org/10.1007/bf00202792

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-1-4757-4067-7openalex-snapshot

Introduction to Applied Nonlinear Dynamical Systems and Chaos

inferredcites →https://doi.org/10.1007/978-1-4757-4067-7_5openalex-snapshot

Some Aspects of Global Bifurcations and Chaos

inferredcites →https://doi.org/10.1007/bf00114845openalex-snapshot

The induction of dynamical recognizers

inferredcites →https://doi.org/10.1007/bf00198101openalex-snapshot

A learning algorithm to teach spatiotemporal patterns to recurrent neural networks

inferredcites →https://doi.org/10.1063/1.4822950openalex-snapshot

Introduction to Applied Nonlinear Dynamical Systems and Chaos

inferredcites →https://doi.org/10.1103/physrevlett.59.2229openalex-snapshot

Generalization of back-propagation to recurrent neural networks

inferredcites →https://doi.org/10.1103/physrevlett.63.105openalex-snapshot

Inferring statistical complexity

inferredcites →https://doi.org/10.1142/0674openalex-snapshot

Elementary Symbolic Dynamics and Chaos in Dissipative Systems

inferredcites →https://doi.org/10.1162/neco.1992.4.3.393openalex-snapshot

Learning and Extracting Finite State Automata with Second-Order Recurrent Neural Networks

inferredcites →https://doi.org/10.1207/s15516709cog1402_1openalex-snapshot

Finding Structure in Time

inferredcites →https://doi.org/10.21236/ada164453openalex-snapshot

Learning Internal Representations by Error Propagation

inferredcites →https://doi.org/10.7551/mitpress/5236.001.0001openalex-snapshot

Parallel Distributed Processing

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Learning to Generate Combinatorial Action Sequences Utilizing the Initial Sensitivity of Deterministic Dynamical Systems

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Essential dynamical structure in learnable autonomous robots

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Towards Robustness to Fluctuated Perceptual Patterns by a Deterministic Predictive Coding Model in a Task of Imitative Synchronization with Human Movement Patterns

inferred← citeshttps://doi.org/10.1007/978-3-319-70090-8_77openalex-snapshot

Bridging the Gap Between Probabilistic and Deterministic Models: A Simulation Study on a Variational Bayes Predictive Coding Recurrent Neural Network Model

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Symbols and Dynamics in Embodied Cognition: Revisiting a Robot Experiment

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Artificial life and real world computing

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A cognitive architecture that combines internal simulation with a global workspace

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Learning to generate combinatorial action sequences utilizing the initial sensitivity of deterministic dynamical systems

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Dynamic and interactive generation of object handling behaviors by a small humanoid robot using a dynamic neural network model

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Learning to imitate stochastic time series in a compositional way by chaos

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An Improved Computer Interface Comprising a Recurrent Neural Network and a Natural User Interface

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Artificial intelligence system for supporting soil classification

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Imitating others by composition of primitive actions: A neuro-dynamic model

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Dynamics of internal models in game players

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Model-based learning for mobile robot navigation from the dynamical systems perspective

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Extracting finite-state representations from recurrent neural networks trained on chaotic symbolic sequences

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Financial volatility trading using recurrent neural networks

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Learning to Perceive the World as Probabilistic or Deterministic via Interaction With Others: A Neuro-Robotics Experiment

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Designing spontaneous behavioral switching via chaotic itinerancy

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Simple Recurrent Networks Learn Context-Free and Context-Sensitive Languages by Counting

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A Novel Predictive-Coding-Inspired Variational RNN Model for Online Prediction and Recognition

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Representation Learning of Logic Words by an RNN: From Word Sequences to Robot Actions

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Action and Intelligence. Cognition and Autonomy of Robots: A Dynamical Systems Perspective.

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Chaos and Robots. Chaos in Robot Learning.

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Cognitive Robotics. The constructivist approach towards the problems of "self" and "self consciousness".

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Studies of Symbols from "Robot Science"

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