Journal ArticleDOI
Neuronlike adaptive elements that can solve difficult learning control problems
Andrew G. Barto,Richard S. Sutton,Charles W. Anderson +2 more
- Vol. 13, Iss: 5, pp 834-846
TLDR
In this article, a system consisting of two neuron-like adaptive elements can solve a difficult learning control problem, where the task is to balance a pole that is hinged to a movable cart by applying forces to the cart base.Abstract:
It is shown how a system consisting of two neuronlike adaptive elements can solve a difficult learning control problem. The task is to balance a pole that is hinged to a movable cart by applying forces to the cart's base. It is argued that the learning problems faced by adaptive elements that are components of adaptive networks are at least as difficult as this version of the pole-balancing problem. The learning system consists of a single associative search element (ASE) and a single adaptive critic element (ACE). In the course of learning to balance the pole, the ASE constructs associations between input and output by searching under the influence of reinforcement feedback, and the ACE constructs a more informative evaluation function than reinforcement feedback alone can provide. The differences between this approach and other attempts to solve problems using neurolike elements are discussed, as is the relation of this work to classical and instrumental conditioning in animal learning studies and its possible implications for research in the neurosciences.read more
Citations
More filters
Journal ArticleDOI
Structure in the Space of Value Functions
David J. Foster,Peter Dayan +1 more
TL;DR: Evidence is presented that fragmentations found using unsupervised, mixture model, learning methods on data derived from optimal value functions for multiple tasks can be of use in a practical reinforcement learning context by facilitating online, actor-critic learning of multiple goals MDPs.
Journal ArticleDOI
Perspectives of approximate dynamic programming
TL;DR: There is actually a common theme to these strategies, and underpinning the entire field remains the fundamental algorithmic strategies of value and policy iteration that were first introduced in the 1950’s and 60s.
Proceedings ArticleDOI
Reinforcement learning of dynamic motor sequence: learning to stand up
Jun Morimoto,Kenji Doya +1 more
TL;DR: This work proposes a learning method for implementing human-like sequential movements in robots using reinforcement learning, in particular, a continuous time and state temporal difference (TD) learning method.
Journal ArticleDOI
Adaptive critic autopilot design of Bank-to-turn missiles using fuzzy basis function networks
TL;DR: The proposed tuning algorithm can significantly shorten the learning time by online tuning all parameters of fuzzy basis functions and weights of ASE and ACE and is capable of guaranteeing both tracking performance and stability.
Proceedings ArticleDOI
Reinforcement structure/parameter learning for neural-network-based fuzzy logic control systems
Chin-Teng Lin,C.S.G. Lee +1 more
TL;DR: The authors propose a reinforcement neural-network-based fuzzy logic control system (RNN-FLCS) for solving various reinforcement learning problems and finds it best applied to learning environments where obtaining exact training data is expensive.
References
More filters
Journal ArticleDOI
Receptive fields, binocular interaction and functional architecture in the cat's visual cortex
David H. Hubel,Torsten N. Wiesel +1 more
TL;DR: This method is used to examine receptive fields of a more complex type and to make additional observations on binocular interaction and this approach is necessary in order to understand the behaviour of individual cells, but it fails to deal with the problem of the relationship of one cell to its neighbours.
Journal ArticleDOI
A Theory of Cerebellar Cortex
TL;DR: A detailed theory of cerebellar cortex is proposed whose consequence is that the cerebellum learns to perform motor skills and two forms of input—output relation are described, both consistent with the cortical theory.
Journal ArticleDOI
Receptive fields and functional architecture in two nonstriate visual areas (18 and 19) of the cat.
David H. Hubel,Torsten N. Wiesel +1 more
TL;DR: To UNDERSTAND VISION in physiological terms represents a formidable problem for the biologist, and one approach is to stimulate the retina with patterns of light while recording from single cells or fibers at various points along the visual pathway.
Journal ArticleDOI
Toward a modern theory of adaptive networks: Expectation and prediction.
TL;DR: The adaptive element presented learns to increase its response rate in anticipation of increased stimulation, producing a conditioned response before the occurrence of the unconditioned stimulus, and is in strong agreement with the behavioral data regarding the effects of stimulus context.
Journal ArticleDOI
Steps toward Artificial Intelligence
TL;DR: The problems of heuristic programming can be divided into five main areas: Search, Pattern-Recognition, Learning, Planning, and Induction as discussed by the authors, and the most successful heuristic (problem-solving) programs constructed to date.