--- title: "Tom Schaul · Google DeepMind — author profile and papers" description: "Tom Schaul, Google DeepMind: 2 papers on Elamur Research (2016–2024), h-index 40 — affiliations, topics, co-authors and who cites them…" canonical: "https://research.elamur.ai/free/en/authors/tom-schaul/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/tom-schaul/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Tom Schaul # Tom Schaul Tom Schaul has 2 papers in our library, in 2016–2024; often with [David Silver](https://md.research.elamur.ai/free/en/authors/david-silver/), [Edward Hughes](https://md.research.elamur.ai/free/en/authors/edward-hughes/), [Feryal Behbahani](https://md.research.elamur.ai/free/en/authors/feryal-behbahani/). 2 papers in our library · 2016–2024 [OpenAlex](https://openalex.org/A5081322018) · [ORCID](https://orcid.org/0000-0002-2961-8782) · [**h-index 40**](https://openalex.org/authors/A5081322018) · [140 works](https://openalex.org/works?filter=author.id:A5081322018) · [17,247 citations](https://openalex.org/works?filter=author.id:A5081322018&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/tom-schaul/#papers) · [🔗 Cited 239 times in our library](https://md.research.elamur.ai/free/en/authors/tom-schaul/cited-by/) · [6 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #5451](https://md.research.elamur.ai/free/en/paper-stars/page/55/#star-5451) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Tom+Schaul) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Tom+Schaul) · [dblp](https://dblp.org/search?q=Tom+Schaul) · [ACL Anthology](https://aclanthology.org/search/?q=Tom+Schaul) ## Affiliations [🏢**Google DeepMind** London · United Kingdom 2008–2025 · 33 papers*current*](https://md.research.elamur.ai/free/en/companies/google-deepmind/) · [🔬**Dalle Molle Institute for Artificial Intelligence Research** Lugano · Switzerland 2008–2011 · 21 papers](https://md.research.elamur.ai/free/en/labs/dalle-molle-institute-for-artificial-intelligence-research/) · [🎓**New York University** New York · United States 2012–2015 · 17 papers](https://md.research.elamur.ai/free/en/universities/new-york-university/) · [🏢**Google** Mountain View · United States 2015–2020 · 14 papers](https://md.research.elamur.ai/free/en/companies/google/) · [🎓**Università della Svizzera italiana** Lugano · Switzerland 2010–2011 · 9 papers](https://md.research.elamur.ai/free/en/universities/universita-della-svizzera-italiana/) · [🎓**Courant Institute of Mathematical Sciences** New York · United States 2012–2014 · 8 papers](https://md.research.elamur.ai/free/en/universities/courant-institute-of-mathematical-sciences/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed. ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 4 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Safety Research · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/safety-research/) · [Social Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/) ## Works by year ### 2020s [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/tom-schaul/year/2024/) ### 2010s [**2016** 1 paper](https://md.research.elamur.ai/free/en/authors/tom-schaul/year/2016/) ## Papers The most cited first (OpenAlex and our library). 1. **[Reinforcement Learning with Unsupervised Auxiliary Tasks](https://md.research.elamur.ai/free/en/papers/jaderberg-2016-reinforcement-learning-unsupervised-auxiliary-tasks/)** *(2016 · 319 citations)* Deep RL agents usually learn only from extrinsic reward, which is often sparse. That leaves most of the information in an agent's observation stream unused. Jaderberg et al. (DeepMind) propose UNREAL (UNsupervised REinforcement and Auxiliary Learning), which extends the A3C actor-critic with extra objectives that… 2. **[Open-Endedness is Essential for Artificial Superhuman Intelligence](https://md.research.elamur.ai/free/en/papers/hughes-2024-open-endedness-essential-artificial-superhuman/)** *(2024 · 14 citations)* This position paper from Google DeepMind (ICML 2024) asks what an AI system would need in order to keep generating new knowledge by itself. ## All works 8 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them. 1. **[StarCraft II: A New Challenge for Reinforcement Learning ↗](https://arxiv.org/abs/1708.04782) arXiv (Cornell University) · no summary yet**Oriol Vinyals et al.*2017 · 680 citations* 2. [**Reinforcement Learning with Unsupervised Auxiliary Tasks arXiv:1611.05397**Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, et al.*2016 · 319 citations*](https://md.research.elamur.ai/free/en/papers/jaderberg-2016-reinforcement-learning-unsupervised-auxiliary-tasks/) 3. **[Unifying Count-Based Exploration and Intrinsic Motivation ↗](https://arxiv.org/abs/1606.01868) arXiv:1606.01868 · no summary yet**Marc G. Bellemare et al.*2016 · 311 citations* 4. **[FeUdal Networks for Hierarchical Reinforcement Learning ↗](https://arxiv.org/abs/1703.01161) arXiv (Cornell University) · no summary yet**Alexander Vezhnevets et al.*2017 · 272 citations* 5. **[General Video Game AI: Competition, Challenges and Opportunities ↗](https://doi.org/10.1609/aaai.v30i1.9869) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Diego Pérez-Liébana et al.*2016 · 178 citations* 6. **[Stochastic search using the natural gradient ↗](https://doi.org/10.1145/1553374.1553522) International Conference on Machine Learning · no summary yet**Yi Sun et al.*2009 · 81 citations* 7. [**Open-Endedness is Essential for Artificial Superhuman Intelligence arXiv:2406.04268**Edward Hughes, Michael Dennis, Jack Parker-Holder, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/hughes-2024-open-endedness-essential-artificial-superhuman/) 8. **[DataRater: Meta-Learned Dataset Curation ↗](https://doi.org/10.52202/085713-0677) neural information processing systems · no summary yet**Dan A. Calian et al.*2025 · 4 citations* ## Co-authors here 9 co-authors with a page, the most papers together first. - [David Silver](https://md.research.elamur.ai/free/en/authors/david-silver/) - [Edward Hughes](https://md.research.elamur.ai/free/en/authors/edward-hughes/) - [Feryal Behbahani](https://md.research.elamur.ai/free/en/authors/feryal-behbahani/) - [Joel Z Leibo](https://md.research.elamur.ai/free/en/authors/joel-z-leibo/) - [Koray Kavukcuoglu](https://md.research.elamur.ai/free/en/authors/koray-kavukcuoglu/) - [Max Jaderberg](https://md.research.elamur.ai/free/en/authors/max-jaderberg/) - [Tim Rocktaschel](https://md.research.elamur.ai/free/en/authors/tim-rocktaschel/) - [Volodymyr Mnih](https://md.research.elamur.ai/free/en/authors/volodymyr-mnih/) - [Wojciech Marian Czarnecki](https://md.research.elamur.ai/free/en/authors/wojciech-marian-czarnecki/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - International Conference on Machine Learning - Proceedings of the AAAI Conference on Artificial Intelligence - neural information processing systems ## Cited by Papers of our library cite their works 239 times (of the 149,439 papers whose bibliographies we read); [35 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/tom-schaul/cited-by/). Updated 3 November 2026