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#ReinforcementLearning

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My colleagues at TU Delft are seeking to hire a postdoc to work on Applied Planning and Scheduling under Uncertainty, with applications in modelling supply chain scenarios for offshore wind farm installation: careers.tudelft.nl/job/Delft-P

careers.tudelft.nlPostdoc in Applied Planning and Scheduling under UncertaintyPostdoc in Applied Planning and Scheduling under Uncertainty

New instance, new #introduction!

I'm a #DataScientist with a background in #ReinforcementLearning and #ElectricalEngineering. Well, that's what my resume says, but really I'm a #poet and a SF/F #writer. I love to play #DnD and other #TTRPGs.

I use they/them pronouns, and "Dr." not "Mr.", please and thank you.

I maintain a blog at www.seanpatrick.phd which includes a current list of publications, including my debut sonnet collection, "Love, Death, and Other Surprises."

#AI #MachineLearning #BiasInAI #STEMSaturday #DeepLearning #ComputerVision #Robotics #ReinforcementLearning

Meet the editors of "Mitigating Bias in Machine Learning" Dr. Carlotta Berry and Dr. Brandeis Hill Marshall (Brandeis Marshall, PhD)
This practical guide shows, step by step, how to use machine learning to carry out actionable decisions that do not discriminate based on numerous human factors, including ethnicity and gender.
On Sale On Amazon a.co/d/dtMizVH

A fun part of working on a #ReinforcementLearning workbench is that I get to think about how to connect different kinds of agents to different kinds of worlds – representation, interfaces, abstraction.

Something I’m stumbling on is representing models and planners.
Is there such a thing as a planner distinct from a model? Or is planning just something a model does?
In object-oriented programming terms, would a planner be a separate class from a model? Or would it be a method in a model class?

MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning

Samvelyan et al.: arxiv.org/abs/2303.03376

arXiv.orgMAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement LearningOpen-ended learning methods that automatically generate a curriculum of increasingly challenging tasks serve as a promising avenue toward generally capable reinforcement learning agents. Existing methods adapt curricula independently over either environment parameters (in single-agent settings) or co-player policies (in multi-agent settings). However, the strengths and weaknesses of co-players can manifest themselves differently depending on environmental features. It is thus crucial to consider the dependency between the environment and co-player when shaping a curriculum in multi-agent domains. In this work, we use this insight and extend Unsupervised Environment Design (UED) to multi-agent environments. We then introduce Multi-Agent Environment Design Strategist for Open-Ended Learning (MAESTRO), the first multi-agent UED approach for two-player zero-sum settings. MAESTRO efficiently produces adversarial, joint curricula over both environments and co-players and attains minimax-regret guarantees at Nash equilibrium. Our experiments show that MAESTRO outperforms a number of strong baselines on competitive two-player games, spanning discrete and continuous control settings.

#introduction : I am a #neuroscientist studying #3dvision in freely moving humans (lots of 3D researchers study static humans or freely moving rats). I am excited by the #cerebellum (which is computionally huge but hard to study electrophysiologically), less so by the #hippocampus (which has been studied in immense detail but may, in the end, have a more minor computational role). I follow #NeuroAI as #machinelearning and #reinforcementlearning may solve the brain, en passant, before we do.

#introduction - I'm a #scientist whose research focused on #ReinforcementLearning . I pivoted out of academia and into #DataScience last year and have no regrets.

For fun I write #ScienceFiction and #Fantasy (especially #PostApocalyptic stories) as well as #poetry, and I'd love to meet the Mastodon #WritingCommunity. Big on #gaming, #DnD and #TTRPG.

I identify as #queer #nonbinary #bisexual and #asexual, I use they/them pronouns.

Say hi!

#introduction

👋 Hi all! I'm an Assistant Professor and Faculty Fellow at NYU's Center for Data Science.

My research aims to develop methods and theoretical insights that enable the safe deployment of ML systems in safety-critical settings by drawing on tools from #ProbabilisticInference, #Optimization, and #ReinforcementLearning. I also work on #AIPolicy.

For more details about my research, check out my website (timrudner.com) or this recent faculty profile: nyudatascience.medium.com/meet!

Tim G. J. RudnerTim G. J. RudnerHomepage of Tim G. J. Rudner

Hi all!

I am a #reinforcementlearning focused PhD Student at UW-Madison, focused on Sim2Real Robotics as applied to robot soccer. In my free time, I like to work on free and #opensource software (particularly OpenAI gym and Farama Foundation Gymnasium).

It's very exciting to see the Mastodon Fediverse getting more users; I think that federated social media presents a compelling alternative to centralized social media, and I'm excited to see if the Fediverse can compete with Twitter at scale.