David Abel

@dabelcs.bsky.social

Scientist @ DeepMind and Honorary Fellow @ U of Edinburgh. RL, agency, philosophy, foundations, alignment. https://david-abel.github.io

Excited to share a new preprint, accepted as a spotlight at #NeurIPS2025! Humans are imperfect decision-makers, and autonomous systems should understand how we deviate from idealized rationality Our paper aims to address this! 👀🧠✨ arxiv.org/abs/2510.25951 a 🧵⤵️

Estimating cognitive biases with attention-aware inverse planning

People's goal-directed behaviors are influenced by their cognitive biases, and autonomous systems that interact with people should be aware of this. For example, people's attention to objects in their...

arxiv.org

Hello world! This is the RL & Agents Reading Group We organise regular meetings to discuss recent papers in Reinforcement Learning (RL), Multi-Agent RL and related areas (open-ended learning, LLM agents, robotics, etc). Meetings take place online and are open to everyone 😊

New paper with Iason Gabriel on "Characterizing AI agents" is out! 2025 is being called the year of AI agents, with overwhelming headlines about them every day. But we lack a shared vocabulary to distinguish their fundamental properties. Our paper aims to bridge this gap. A 🧵

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new paper: "Evolution and the Knightian Blindspot of Machine Learning" Our ever-changing world bubbles with surprise and complexity. General AI must include handling unforeseen situations with grace. Yet this issue largely lies outside AI's formalisms: a blind spot. (1/n)

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Are there limits to what you can learn in a closed system? Do we need human feedback in training? Is scale all we need? Should we play language games? What even is "recursive self-improvement"? Thoughts about this and more here: arxiv.org/abs/2411.16905

Boundless Socratic Learning with Language Games

An agent trained within a closed system can master any desired capability, as long as the following three conditions hold: (a) it receives sufficiently informative and aligned feedback, (b) its covera...

arxiv.org

Have ideas for an interdisciplinary workshop? Get involved at RLDM to tackle key challenges, open problems, or controversial topics! 🎤 Formats: Talks, panels, hackathons, debates—your choice! 👥 All career stages welcome to lead. 🗓️ Deadline to apply: 10th December. Link 🔽 rldm.org/call-for-wor...

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