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Joshua Achiam
Joshua Achiam
Research Scientist, OpenAI
Verified email at berkeley.edu - Homepage
Title
Cited by
Cited by
Year
On First-Order Meta-Learning Algorithms
A Nichol, J Achiam, J Schulman
arXiv preprint arXiv:1803.02999, 2018
22572018
Constrained Policy Optimization
J Achiam, D Held, A Tamar, P Abbeel
arXiv preprint arXiv:1705.10528, 2017
13642017
Benchmarking Safe Exploration in Deep Reinforcement Learning
A Ray, J Achiam, D Amodei
https://cdn.openai.com/safexp-short.pdf, 2019
3812019
Surprise-Based Intrinsic Motivation for Deep Reinforcement Learning
J Achiam, S Sastry
arXiv preprint arXiv:1703.01732, 2017
2692017
Spinning Up in Deep Reinforcement Learning
J Achiam
https://spinningup.openai.com, 0
251
Responsive safety in reinforcement learning by pid lagrangian methods
A Stooke, J Achiam, P Abbeel
International Conference on Machine Learning, 9133-9143, 2020
2222020
Variational Option Discovery Algorithms
J Achiam, H Edwards, D Amodei, P Abbeel
arXiv preprint arXiv:1807.10299, 2018
1822018
Towards Characterizing Divergence in Deep Q-Learning
J Achiam, E Knight, P Abbeel
arXiv preprint arXiv:1903.08894, 2019
1072019
A hazard analysis framework for code synthesis large language models
H Khlaaf, P Mishkin, J Achiam, G Krueger, M Brundage
arXiv preprint arXiv:2207.14157, 2022
172022
Advanced Policy Gradient Methods
J Achiam
Lecture [online] http://rail.eecs.berkeley.edu/deeprlcourse-fa17/f17docs …, 2017
52017
Exploration and Safety in Deep Reinforcement Learning
JS Achiam
University of California, Berkeley, 2021
32021
Variational Option Discovery Algorithms By admin No Comments
J Achiam, D Amodei, H Edwards, P Abbeel
Training Dynamics Models for Accurate Long-Horizon Prediction
E Knight, J Achiam, UC OpenAI
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