We are excited to announce the launch of SenseAct, the first reinforcement learning open-source toolkit for physical robots businesswire.com/news/home/2018… #reinforcementlearning #Robotics #machinelearning #robots

Some of my recent work with Rupam Mahmood on real-time vision-based learning from scratch on robots! #Robotics #RL

A packed house to hear Bill Flanagan from the University of Alberta and Amii announce that 20 new faculty will be hired in AI across campus in the next 3 years, with 5 of these positions in CS.

Thank you @neuralbertatech, for organizing the natChat 2023 event and making my invited talk public! youtu.be/kkJ8-k-_CPQ #reinforcementlearning #robotics

#AGIComics offers a definition of AGI that is achievable, based on economics, and provably safe.

Explored some practical, oft-ignored challenges in continual learning on real-world robots in a recent AI Seminar, delving into: 1️⃣ Specifying reinforcement learning tasks 2️⃣ Setting up a real-time learning agent youtu.be/QO0mmHMJvRQ?si… 🤖

Hope to see you at The AAMAS Conference 2024 in New Zealand! Thank you to my co-authors Tristan Tomilin, Gautham Vasan, Matt Taylor, Rupam Mahmood, Meng Fang, Mykola Pechenizkiy, and Decebal Mocanu. 📜arxiv.org/abs/2312.15339 💻github.com/bramgrooten/ma…

Trying to put myself out there more often. Some thoughts on Moravec's paradox, sim-to-real transfer, and robot learning: gauthamvasan.github.io/posts/simulato… Hope you find it interesting! #AI #Robotics

Come checkout our cool poster The AAMAS Conference this week! 🇳🇿

Check out our research on how to specify rewards in RL: TL;DR: Sparse reward formulations can lead to higher-quality policies and outperform dense reward policies on their own metrics. Paper 📜: arxiv.org/abs/2407.00324 #reinforcementlearning #robotics

I'm presenting our work on reward design and robot learning at RLC today! We show that it is possible to learn pixel-based policies from scratch on real robots within two to three hours using only sparse rewards 🤖 📜 arxiv.org/abs/2407.00324 🎞️ youtu.be/a6zlVUuKzBc?si… #RLC

Would you believe that deep RL can work without replay buffers, target networks, or batch updates? Our recent work gets deep RL agents to learn from a continuous stream of data one sample at a time without storing any sample. Joint work with Gautham Vasan and Rupam Mahmood.

I'm in Vancouver for #NeurIPS2024. Ping me if you're around and want to chat about deep RL, robotics, continual learning and such!

I'm giving a talk next week on our recent NeurIPS paper, "Deep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay Buffers". Feel free to join if you are available! :) Thank you Cohere For AI for hosting me! 📜 arxiv.org/abs/2411.15370

Congrats Richard Sutton and Andy! You've built an incredible community and shaped the thinking of many researchers, including myself. Well deserved!

Amii Intelligent Systems If you are interested in working with me at *the* RL powerhouse University of Alberta on robot learning on physical robots, please drop me a message. Retweets welcome 🙏