Tutorial 1: Learning to Predict
Tutorial 1: Learning to Predict
This tutorial presents how to estimate state-value functions in a classical conditioning paradigm using Temporal Difference (TD) learning and examine TD-errors at the presentation of the conditioned and unconditioned stimulus (CS and US) under different CS-US contingencies. These exercises will provide you with an understanding of both how reward prediction errors (RPEs) behave in classical conditioning and what we should expect to see if Dopamine represents a "canonical" model-free RPE.
Topics covered in this lesson
- You will learn to use the standard tapped delay line conditioning model
- You will understand how reward prediction errors (RPEs) move to conditional stimulus (CS)
- You will understand how variability in reward size effects RPEs
- You will understand how differences in conditioned and unconditioned stimulus (US-CS) timing effect RPEs
Prerequisites
Experience with Python Programming Language.
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