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Michael Dennis
Manage episode 283177464 series 2536330
Michael Dennis is a PhD student at the Center for Human-Compatible AI at UC Berkeley, supervised by Professor Stuart Russell.
I'm interested in robustness in RL and multi-agent RL, specifically as it applies to making the interaction between AI systems and society at large to be more beneficial.--Michael Dennis
Featured References
Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design [PAIRED]
Michael Dennis, Natasha Jaques, Eugene Vinitsky, Alexandre Bayen, Stuart Russell, Andrew Critch, Sergey Levine
Videos
Adversarial Policies: Attacking Deep Reinforcement Learning
Adam Gleave, Michael Dennis, Cody Wild, Neel Kant, Sergey Levine, Stuart Russell
Homepage and Videos
Accumulating Risk Capital Through Investing in Cooperation
Charlotte Roman, Michael Dennis, Andrew Critch, Stuart Russell
Quantifying Differences in Reward Functions [EPIC]
Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell, Jan Leike
Additional References
- Safe Opponent Exploitation, Sam Ganzfried And Tuomas Sandholm 2015
- Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning, Natasha Jaques et al 2019
- Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence Research, Leibo et al 2019
- Leveraging Procedural Generation to Benchmark Reinforcement Learning, Karl Cobbe et al 2019
- Paired Open-Ended Trailblazer (POET): Endlessly Generating Increasingly Complex and Diverse Learning Environments and Their Solutions, Wang et al 2019
- Consequences of Misaligned AI, Zhuang et al 2020
- Conservative Agency via Attainable Utility Preservation, Turner et al 2019
61 Episoden
Manage episode 283177464 series 2536330
Michael Dennis is a PhD student at the Center for Human-Compatible AI at UC Berkeley, supervised by Professor Stuart Russell.
I'm interested in robustness in RL and multi-agent RL, specifically as it applies to making the interaction between AI systems and society at large to be more beneficial.--Michael Dennis
Featured References
Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design [PAIRED]
Michael Dennis, Natasha Jaques, Eugene Vinitsky, Alexandre Bayen, Stuart Russell, Andrew Critch, Sergey Levine
Videos
Adversarial Policies: Attacking Deep Reinforcement Learning
Adam Gleave, Michael Dennis, Cody Wild, Neel Kant, Sergey Levine, Stuart Russell
Homepage and Videos
Accumulating Risk Capital Through Investing in Cooperation
Charlotte Roman, Michael Dennis, Andrew Critch, Stuart Russell
Quantifying Differences in Reward Functions [EPIC]
Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell, Jan Leike
Additional References
- Safe Opponent Exploitation, Sam Ganzfried And Tuomas Sandholm 2015
- Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning, Natasha Jaques et al 2019
- Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence Research, Leibo et al 2019
- Leveraging Procedural Generation to Benchmark Reinforcement Learning, Karl Cobbe et al 2019
- Paired Open-Ended Trailblazer (POET): Endlessly Generating Increasingly Complex and Diverse Learning Environments and Their Solutions, Wang et al 2019
- Consequences of Misaligned AI, Zhuang et al 2020
- Conservative Agency via Attainable Utility Preservation, Turner et al 2019
61 Episoden
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