Levi Lelis

@programsynthesis.bsky.social

Associate Professor - University of Alberta Canada CIFAR AI Chair with Amii Machine Learning and Program Synthesis he/him; ele/dele 🇨🇦 🇧🇷 https://www.cs.ualberta.ca/~santanad

Excited to announce that our work on Reinforcement Learning for Arachnophobia treatment has been accepted at ACM Transactions on Interactive Intelligent Systems! We found that an RL agent could more effectively adapt VR spiders to achieve specified anxiety levels in users compared to current SOTA.

A graph showing that a rules-based approach consistently underperformed at achieving desired anxiety levels measured in normalized SCL compared to an RL approach. A brownish red virtual spider a medium distance awayA close by black fuzzy spider

Previous work has shown that programmatic policies—computer programs written in a domain-specific language—generalize to out-of-distribution problems more easily than neural policies. Is this really the case? 🧵

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Previous work has shown that programmatic policies—computer programs written in a domain-specific language—generalize to out-of-distribution problems more easily than neural policies. Is this really the case? 🧵

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If like me your Discover feed has been even worse lately and you are here for ML/AI news and discussion, check out these two feeds: - Paper Skygest - ML Feed: Trending Links below 👇

As AI agents face increasingly long and complex tasks, decomposing them into subtasks becomes increasingly appealing. But how do we discover such temporal structure? Hierarchical RL provides a natural formalism-yet many questions remain open. Here's our overview of the field🧵

As hot as this summer is, it’s also one of the coolest we’ll ever enjoy again. Just how much hotter and deadlier summers will get is still up to us. Right now we’re working hard to make them worse 🎁 link to my @opinion.bloomberg.com column: www.bloomberg.com/opinion/arti...

The Heat Dome Wants a Word With Climate-Change Deniers

The temperatures gripping the US this week were made up to five times more likely by the fact that the atmosphere is simply hotter.

bloomberg.com

Hiring a postdoc to scale up and deploy RL-based planning onto some self-driving cars! We'll be building on arxiv.org/abs/2502.03349 and learn what the limits and challenges of RL planning are. Shoot me a message if interested and help spread the word please! Full posting to come in a bit.

Robust Autonomy Emerges from Self-Play

Self-play has powered breakthroughs in two-player and multi-player games. Here we show that self-play is a surprisingly effective strategy in another domain. We show that robust and naturalistic drivi...

arxiv.org

🧵1/ New paper! 📄 Subgoal-Guided Policy Heuristic Search with Learned Subgoals, led by my PhD student @tuero.ca. arxiv.org/pdf/2506.07255 This paper follows the Levin tree search (LTS) research line and focuses on learning subgoal-based policies.

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Jake Tuero@tuero.ca · last yr.

Excited to share our paper "Subgoal-Guided Policy Heuristic Search with Learned Subgoals" has been accepted to #icml2025! Paper Preview: arxiv.org/pdf/2506.07255 I'll be attending ICML-25 in Vancouver, and I'm looking forward to chatting with anyone who is interested in our work!

We are very happy to report that the second edition of our textbook on Artificial Intelligence and Games is now finally published! This book is a thorough update of our popular textbook, trying to provide a comprehensive coverage of the many aspects of and use cases for AI in games.

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🎉 Super excited: today @sharky6000.bsky.social is presenting our new algorithm Progressive Hiding at #AAMAS2025! It's a learning method for games with imperfect information. 🔗 See his post: bsky.app/profile/shar... Wish I could be there! 😢 1/6

Marc Lanctot@sharky6000.bsky.social · last yr.

Day #5 and last day 😭 @aamasconf.bsky.social We'll be presenting one more paper called "Learning in Games with Progressive Hiding" by @benhey.bsky.social and myself. Poster @ 10am, talk @ 11:30am. arxiv.org/abs/2409.03875 This is an application of progressive hedging to learning in games: 1/2

🎓 PhD position available! Join our interdisciplinary research project on causal agent-based modelling! 🔍 Looking for curious minds with a MSc degree (or near to completing one) in CS/AI/related fields. 📍 Location: Utrecht University, NL 🗓️ Deadline: 16 June 2025 📩 Info: www.uu.nl/en/organisat...

PhD Position in Causal Agent-based Modelling of Complex Social Systems

Join this exciting interdisciplinary research project at the Centre for Complex Systems Studies and study causal agent-based modelling!

uu.nl

A bit of an old paper but I'm still excited about it, I've never posted about it, and we just released code for the main algorithm: Population RL (PopRL). 👇 Population-based Evaluation in Repeated Rock-Paper-Scissors as a Benchmark for Multiagent Reinforcement Learning, accepted (TMLR '23) 🧵 1/N

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