Inverse Reinforcement Learning: An Introduction
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Notes derived from Sergey Levine’s Deep RL course at Berkeley
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Notes derived from Sergey Levine’s Deep RL course at Berkeley
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Code for the purpose of learning reinforcement learning using OpenAI Gym. Topics covered are below.
Published in ACS, 2020
This paper is about using machine learning to learn perovskite reaching when ones model of the chemical world is not accurate
Recommended citation: see below http://aadharna.github.io/files/perovskite.pdf
Published in AIIDE 2020, 2020
This paper is about using coevolution of game-levels and game-playing agents in GVGAI
Recommended citation: see below http://aadharna.github.io/files/PINSKY.pdf
Published in IEEE Transactions on Games 2022, 2022
This paper analyzes the necessity of agent transfer in generated curricula
Recommended citation: see below http://aadharna.github.io/files/Transfer_PINSKY.pdf
Published in ALOE Workshop 2022 @ ICLR, 2022
This paper introduces a software framework to explore open-ended learning algorithms
Recommended citation: see below http://aadharna.github.io/files/watts.pdf
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Published:
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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