Literature Introduction

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Here are some links to websites and papers where you can learn about some of the topics that I supervise master theses within. Note that you should not read up on all these topics. But if any of the topics below are central to your thesis, the links may give you a good place to start looking for knowledge.


Reinforcement Learning

Spinning Up in Deep RL

OpenAI Gym

An overview of some common test environments for RL (see chapter 3)

Intrinsic Motivation in RL

Evolutionary Algorithms (and some related concepts)

DEAP (user-friendly EA Python framework)

Quality Diversity Algorithms

Quality Diversity github

Evolving the behavior of machines: from micro to macroevolution

Open-Ended Evolution

An Overview of Open-Ended Evolution

Paired Open-Ended Trailblazer


Designing Neural Networks through Neuroevolution

NEAT (popular Neuroevolution algorithm) for Python

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