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Reposted by Gaspard Lambrechts

ELLIS @ellis.eu · 04/03/2026

📣 Reinforcement Learning Summer School is returning to Milan in 2026! Co-organized with @ellisunitmilan.bsky.social & designed for Master's and PhD students on RL theory, multi-agent systems, RL & LLMs, real-world applications... 📍 Milan 🇮🇹 📅 3-12 June ⏰ Apply by 27 March 🔗 bit.ly/4b2Plhp

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Gaspard Lambrechts @gsprd.be · 20/02/2026

At NeurIPS, we presented asymmetric RL algo: Asymmetric Advantage Weighted Regression (AAWR). This time, the goal is to learn a policy pi(a | z) whose input z = f(h) is not necessarily Markovian. It is useful in robotics, for example. So, how to adapt RL in POMDP to non Markovian input? 🧵

youtu.be

AAWR: Real World RL of Active Perception Behaviors @ NeurIPS2025

YouTube video by Jie Wang

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Gaspard Lambrechts @gsprd.be · 06/10/2025

At #EWRL, we presented 4 papers, which we summarize below. - A Theoretical Justification for AsymAC Algorithms. - Informed AsymAC: Theoretical Insights and Open Questions. - Behind the Myth of Exploration in Policy Gradients. - Off-Policy MaxEntRL with Future State-Action Visitation Measures.

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Reposted by Gaspard Lambrechts

Théo Vincent @theo-vincent.bsky.social · 19/07/2025

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?...

youtu.be

Théo Vincent - Optimizing the Learning Trajectory of Reinforcement Learning Agents

YouTube video by Cohere

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Reposted by Gaspard Lambrechts

Claire Vernade @claireve.bsky.social · 17/07/2025

Such an inspiring talk by @arkrause.bsky.social at #ICML today. The role of efficient exploration in Scientific discovery is fundamental and I really like how Andreas connects the dots with RL (theory).

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Gaspard Lambrechts @gsprd.be · 16/07/2025

At #ICML2025, we will present a theoretical justification for the benefits of « asymmetric actor-critic » algorithms (#W1008 Wednesday at 11am). 📝 Paper: hdl.handle.net/2268/326874 💻 Blog: damien-ernst.be/2025/06/10/a...

ICML poster of the paper « A Theoretical Justification for Asymmetric Actor-Critic Algorithms » by Gaspard Lambrechts, Damien Ernst and Aditya Mahajan.

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Reposted by Gaspard Lambrechts

Riccardo Zamboni @ricczamboni.bsky.social · 08/07/2025

🌟🌟Good news for the explorers🗺️! Next week we will present our paper “Enhancing Diversity in Parallel Agents: A Maximum Exploration Story” with V. De Paola, @mircomutti.bsky.social and M. Restelli at @icmlconf.bsky.social! (1/N)

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Gaspard Lambrechts @gsprd.be · 11/07/2025

Last week, I gave an invited talk on "asymmetric reinforcement learning" at the BeNeRL workshop. I was happy to draw attention to this niche topic, which I think can be useful to any reinforcement learning researcher. Slides: hdl.handle.net/2268/333931.

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Gaspard Lambrechts @gsprd.be · 13/06/2025

Two months after my PhD defense on RL in POMDP, I finally uploaded the final version of my thesis :) You can find it here: hdl.handle.net/2268/328700 (manuscript and slides). Many thanks to my advisors and to the jury members.

Cover page of the PhD thesis "Reinforcement Learning in Partially Observable Markov Decision Processes: Learning to Remember the Past by Learning to Predict the Future" by Gaspard Lambrechts

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Gaspard Lambrechts @gsprd.be · 09/06/2025

📝 Our paper "A Theoretical Justification for Asymmetric Actor-Critic Algorithms" was accepted at #ICML! Never heard of "asymmetric actor-critic" algorithms? Yet, many successful #RL applications use them (see image). But these algorithms are not fully understood. Below, we provide some insights.

Slide showing three recent successes of reinforcement learning that have used an asymmetric actor-critic algorithm:
- Magnetic Control of Tokamak Plasma through Deep RL (Degrave et al., 2022).
- Champion-Level Drone Racing using Deep RL (Kaufmann et al., 2023).
- A Super-Human Vision-Based RL Agent in Gran Turismo (Vasco et al., 2024).

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Reposted by Gaspard Lambrechts

EWRL @ewrl-org.bsky.social · 26/05/2025

📢 Deadline extended! Submit your work to EWRL — now accepting papers until June 3rd AoE. This year, we're also offering a fast track for papers accepted at other conferences ⚡ Check the website for all the details: euro-workshop-on-reinforcement-learning.github.io/ewrl18/

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Gaspard Lambrechts @gsprd.be · 03/04/2025

Slydst, my Typst package for making simple slides, just got its 100th star on Github. While I would not advise using Typst for papers yet, its markdown-like syntax allows to create slides in a few minutes, while supporting everything we love from LaTeX: equations. github.com/glambrechts/...

Typst interface showing an example of Slydst code and the resulting slides.

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Reposted by Gaspard Lambrechts

Gilles Louppe @glouppe.bsky.social · 30/12/2024

📣 Hiring! I am looking for PhD/postdoc candidates to work on foundation models for science at @ULiege, with a special focus on weather and climate systems. 🌏 Three positions are open around deep learning, physics-informed FMs and inverse problems with FMs.

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Reposted by Gaspard Lambrechts

Adrien Bolland @adrienbolland.bsky.social · 13/12/2024

Check our work on max entropy RL! We introduce an off-policy method to maximize the entropy of the future state-action visitation distribution, leading to policies that explore effectively and achieve high performance 🎯 Link 📑 arxiv.org/abs/2412.06655 #RL #MaxEntRL #Exploration

arxiv.org

Off-Policy Maximum Entropy RL with Future State and Action Visitation Measures

We introduce a new maximum entropy reinforcement learning framework based on the distribution of states and actions visited by a policy. More precisely, an intrinsic reward function is added to the re...

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Gaspard Lambrechts @gsprd.be · 03/12/2024

How come I didn't know about this BeNeRL seminar series? It focuses on practical RL and seems really great! www.benerl.org/seminar-seri... I would have loved to hear Benjamin Eysenbach, Chris Lu and Edward Hu... Next one is on December 19th.

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Gaspard Lambrechts @gsprd.be · 26/11/2024

Hi Bluesky! I'm a PhD student researching #RL in #POMDP. If you're also interested in: - sequence models, - world models, - representation learning, - asymmetric learning, - generalization, I'd love to connect, chat, or check out your work! Feel free to reply or message me.

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