RL computational models

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Table of contents

1 Introduction
1.2 Objectives
1.3 Methods
1.4 Organization
2 Reinforcement learning
2.1 Introduction
2.2 Markov Decision Processes
2.3 Reinforcement learning
2.4 Extensions of the classical framework – Factored representations
3 Animal conditioning
3.1 Introduction
3.2 Instrumental conditioning
3.3 Pavlovian conditioning
3.4 Pavlovian-instrumental interactions
4 Synthesis and working hypothesis
5 Modelling individual differences in autoshaping CRs (article) 
6 Predictions from a computational model of autoshaping (article) 
Abstract
Introduction
Material and methods
Results
Discussion
7 Model of individual differences in negative automaintenance (article) 
Abstract
Introduction
Methods
Results
Discussion
8 Discussion 
8.1 Contributions synthesis
8.2 Limits and perspectives
8.3 Concluding remarks