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Book ChapterDOI

The Role of the Critic in Learning Systems

TLDR
This article analyzes the three tasks of the Critic as threefold: evaluation of the past actions of the performance element of the learning system, localization of credit and blame to particular portions of that performance element, and recommendation of possible improvements and modifications in the performanceelement.
Abstract
Buchanan, Mitchell, Smith, and Johnson (1978) described a general model of learning systems that included a component called the Critic. The task of the Critic was described as threefold: evaluation of the past actions of the performance element of the learning system, localization of credit and blame to particular portions of that performance element, and recommendation of possible improvements and modifications in the performance element. This article analyzes these three tasks in detail and surveys the methods that have been employed in existing learning systems to accomplish them. The principle method used to evaluate the performance element is to develop a global performance standard by (a) consulting an external source of knowledge, (b) consulting an internal source of knowledge, or (c) conducting deep search. Credit and blame have been localized by (a) asking an external knowledge source to do the localization, (b) factoring the global performance standard to produce a local performance standard, and (c) conducting controlled experiments on the performance element. Recommendations have been conmiunicated to the learning element using (a) local training instances, (b) correlation coefficients, and (c) partially-instantiated schemata.

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Citations
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Book

Reinforcement Learning: An Introduction

TL;DR: This book provides a clear and simple account of the key ideas and algorithms of reinforcement learning, which ranges from the history of the field's intellectual foundations to the most recent developments and applications.
Journal ArticleDOI

Neuronlike adaptive elements that can solve difficult learning control problems

TL;DR: 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.
Journal ArticleDOI

A method for attribute selection in inductive learning systems

TL;DR: A computable measure was developed that can be used to discriminate between attributes on the basis of their potential value in the formation of decision rules by the inductive learning process and a significant reduction in the number of attributes to be considered was achieved for a complex medical domain.
Book

Acquiring strategic knowledge from experts

TL;DR: In this paper, strategic knowledge is used to decide what course of action to take, when there are confiicting criteria to satisfy and the effects of actions are not known in advance.
Dissertation

Apprenticeship learning techniques for knowledge based systems

TL;DR: The Odysseus learning program provides the first demonstration of using the same technique to transfer of expertise to and from an expert system knowledge base, and the synthetic agent method is presented, which provides a means of determining a performance upper bound for an apprenticeship learning system.
References
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Book

The Handbook of Artificial Intelligence

TL;DR: Part 1 of a three volume set that contains some 200 articles on AI as discussed by the authors discusses the goals of AI research, the history of the field and the current active areas of research.
Dissertation

Learning Structural Descriptions From Examples

TL;DR: In this paper, the authors propose a method to solve the problem of energy efficiency in the context of electrical engineering, and demonstrate that it can be achieved by using energy minimization techniques.
Journal ArticleDOI

Learning and executing generalized robot plans

TL;DR: Some major new additions to the STRIPS robot problem-solving system are described, including a process for generalizing a plan produced by STriPS so that problem-specific constants appearing in the plan are replaced by problem-independent parameters.
Book

Computers and Thought

TL;DR: Computers and Thought as mentioned in this paper is a collection of twenty classic papers by such pioneers as A. M. Turing and Marvin Minsky who were behind the pivotal advances in artificially simulating human thought processes with computers.
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