Reinforcement learning is a self-evolving type of machine learning that takes us closer to achieving true artificial intelligence. This easy-to-follow guide explains everything from scratch using rich examples written in Python.
Learning and Reinforcement
โ Scribed by Stephen Walker
- Publisher
- Methuen
- Year
- 1975
- Tongue
- English
- Leaves
- 110
- Series
- Essential Psychology
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Table of Contents
Front Cover......Page 1
Copyright......Page 2
Contents......Page 3
1. Introduction......Page 4
2. Habituation: the difference between familiar and unfamiliar stimuli......Page 13
3. Classical conditioning: involuntary associations......Page 22
reward andpositive reinforcement......Page 32
4. Operant conditioning: reward and positive reinforcement......Page 31
5. Operant conditioning: negative reinforcement and punishment......Page 46
6. Intermittent reinforcement and extinction: scarcity and absence of reinforcers......Page 58
7. Primary and secondary reinforcers: where do they come from?......Page 65
8. Discrimination learning: reinforcement for paying attention......Page 75
9. Concept learning: reinforcement for abstract behaviour......Page 86
Further reading......Page 98
References and Name Index......Page 99
Subject Index......Page 107
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Reinforcement learning is a self-evolving type of machine learning that takes us closer to achieving true artificial intelligence. This easy-to-follow guide explains everything from scratch using rich examples written in Python.;Cover; Title Page; Copyright and Credits; Dedication; Packt Upsell; Con
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Reinforcement learning is a self-evolving type of machine learning that takes us closer to achieving true artificial intelligence. This easy-to-follow guide explains everything from scratch using rich examples written in Python.;Cover; Title Page; Copyright and Credits; Dedication; Packt Upsell; Con