Why do we keep using semi-gradient methods when they can diverge?🤨 Gradient TD methods are often overlooked, while they have convergence guarantees! @rl-conference.bsky.social, we will present the first gradient TD method shown to be competitive against semi-gradient methods on deep RL benchmarks🏆

Really excited about the talks, discussions, and reading the submitted works!

We are proud to have an amazing line-up of speakers! They will present their works, which incorporate the constraint that the world is bigger than the agent and impossible to anticipate, observe, or model perfectly. We are also looking forward to the panel discussion!

I had an amazing time today visiting Professor Luiz Chaimowicz's lab in Belo Horizonte! I really enjoyed discovering the research being done at UFMG. It seems to be an amazing place to do some research! See you @iclr-conf.bsky.social in Rio

I will be presenting 3 papers @iclr-conf.bsky.social this week 🇧🇷 Looking forward to some interesting exchanges!

🌍World models can play an important role towards building general agents, but what should be their role in decision-making?🕹️ @joemwatson.bsky.social and I are organizing a Social @iclr-conf.bsky.social on this topic🎙️ 🗓️Feel free to join the conversation on Friday 24th April, at noon!!

Working with constrained agents in complex environments? Do not hesitate to submit your latest work to this workshop! See you in Montréal @rl-conference.bsky.social 🇨🇦

A bunch of us are organizing a workshop at RLC. If your goal is to develop algorithms that allow agents to learn from complex data streams without relying on human data and human designers, then this workshop would be a good fit.

Really excited to organize this workshop! Many works overlook the complexity ratio between the agent and its environment, often leading to overpowered agents. If we want agents to learn continuously in the wild, we need to care about this ratio!

RL in Big Worlds is a workshop at @rl-conference.bsky.social about ideas that enable agents to achieve goals in environments vastly more complex than themselves. This requires giving agents the ability to learn continually and use approximate value functions, models, and policies effectively.

Benchmarking always takes a ton of time😮‍💨 and we often hear about it🗣️ But we rarely report the carbon footprint of experiments, which better reflects their weight! Here is the electricity emission of the experiments in each paper of my PhD👇

Quick reminder for everyone grinding on their RLC 2026 papers, only ~3 weeks to go! The submission site opens in just a few days (Feb 17). Deadlines: ⏳ March 1 (AoE): Abstract Submission ⏳ March 5 (AoE): Full Paper Submission Good luck with the final changes!

We're thrilled to share that the Call for Workshops for this year's @rl-conference.bsky.social is now live! As Workshop co-chair (alongside the wonderful Raksha Kumaraswamy and @claireve.bsky.social) we are looking forward to seeing the proposals for workshops that we receive. LINK IN NEXT POST

🧵 Accepted at @iclr-conf.bsky.social! Target networks stabilize bootstrapping in RL 🛡️ But induce slow-moving targets 🐢 Online networks adapt fast ⚡ But can diverge with function approximation 💥 𝗠𝗜𝗡𝗧𝗢 🌿 uses the online network 𝗼𝗻𝗹𝘆 𝗶𝗳 𝗶𝘁 𝗰𝗮𝗻 — yielding faster 𝘢𝘯𝘥 more stable RL. Here’s how 👇

The Reinforcement Learning workshop at U Mannheim was a lot of fun and highly recommended if you are looking for an engaging exchange of ideas, thanks to the organizers: Leif Döring, @theo-vincent.bsky.social, @claireve.bsky.social, and Simon Weißmann! www.wim.uni-mannheim.de/doering/conf...

Should we use a target network in deep value-based RL?🤔 The answer has always been YES or NO, as there are pros and cons. @iclr-conf.bsky.social, I will present iS-QN, a method that lies in between this binary view, collecting the pros while reducing the cons🚀

🥳Our paper "Floating-Base Deep Lagrangian Networks (FeLaN)" has been accepted to #ICRA2026. FeLaN: a grey-box approach for physically consistent SysID of floating-base robots (humanoids, quadrupeds). 📄 arxiv.org/abs/2510.17270 💻 Soon! 🌐 schulze18.github.io/felan_website/

Ahmed Hendawy, Henrik Metternich, Th\'eo Vincent, Mahdi Kallel, Jan Peters, Carlo D'Eramo: Use the Online Network If You Can: Towards Fast and Stable Reinforcement Learning https://arxiv.org/abs/2510.02590 https://arxiv.org/pdf/2510.02590 https://arxiv.org/html/2510.02590

🎤 Announcing the 3rd workshop on Reinforcement Learning in Mannheim 🎤 We have an amazing lineup of speakers: @Mathieugeist, @gio_ramponi, Theresa Eimer, @SarahKeren_, @araffin2, @c_rothkopf, and @AdrienBolland ⏰ Friday 6th February 📍University of Mannheim

New #J2C Certification: Iterated $Q$-Network: Beyond One-Step Bellman Updates in Deep Reinforcement Learning Théo Vincent, Daniel Palenicek, Boris Belousov, Jan Peters, Carlo D'Eramo https://openreview.net/forum?id=Lt2H8Bd8jF #reinforcement #iterative #iterations

As usual, @ewrl18.bsky.social was a wonderful experience. I had the pleasure of presenting my research as a Contributed Talk 🎉 Special thanks to the organizers for making it happen!

Looking forward to @rl-conference.bsky.social ! I will be presenting 4 posters. Feel free to come and exchange with me during the conference, at the Finding the Frame workshop, or at the Inductive Biases workshop🙂

Had an amazing time presenting my research @cohereforai.bsky.social yesterday 🎤 In case you could not attend, feel free to check it out 👉 youtu.be/RCA22JWiiY8?...

🎤 Very excited to give a talk @cohereforai.bsky.social next week Friday 🎤 I will be presenting the research I have been working on for the last 2 years with Carlo D'Eramo, @jan-peters.bsky.social, and many more collaborators!

IAS is at RLDM 2025! We have many exiting works to share (see 👇), so come to our posters and talk to us!

Sparse network -> sparse poster I will be presenting Eau De Q-Network today @rldmdublin2025.bsky.social Feel free to come and exchange at Poster #28 🎤 bsky.app/profile/theo...

Excited to present our latest work at RLDM 2025! If you’re curious about tactile sensing, active perception, or RL in robotics, stop by my poster. Here’s what we’ve been up to: 🧵 #Robotics #TactileSensing #ReinforcementLearning #Transformers #ActivePerception @ias-tudarmstadt.bsky.social

Very excited to present 🎉Eau De Q-Network🎉 on Thursday @rldmdublin2025.bsky.social Poster #28 🔍Eau De Q-Network gradually prunes the network weights at the agent's learning pace, ultimately reaching a final sparsity level that is discovered by the algorithm!🔎 👉📰 arxiv.org/pdf/2503.01437

Learn more at the workshop website: egoact.github.io/rss2025 Happy to be organizing this with @georgiachal.bsky.social, Yu Xiang, @danfei.bsky.social and @galasso.bsky.social!

Very happy to announce that iterated Q-Network (i-QN) has been published in TMLR 🎉 i-QN learns several Bellman iterations in parallel instead of learning them sequentially via repeated target updates ✨ This directly translates to performance improvements on the Atari and MuJoCo benchmarks 🚀

Iterated $Q$-Network: Beyond One-Step Bellman Updates in Deep Reinforcement Learning Théo Vincent, Daniel Palenicek, Boris Belousov, Jan Peters, Carlo D'Eramo Action editor: Pablo Castro https://openreview.net/forum?id=Lt2H8Bd8jF #reinforcement #iterative #iterations

The RL (and some non-RL folks) starter pack is almost full. Pretty clear that the academic move here has succeeded go.bsky.app/3WPHcHg