I am currently a research scientist at Google DeepMind.

Previously, I was a Ph.D. student in the Gatsby Computational Neuroscience Unit (UCL, London, UK), where I was supervised by Peter Dayan and David Silver.

In 2014, I was interning at Microsoft Research Cambridge. In 2008-2010, I was a M.Sc. student in Computer Science at McGill University in Montréal. My research supervisor was Joelle Pineau. I was part of the Reasoning and Learning lab and I was a member of the McGill Center for Intelligent Machines.

Publications

Theses:
  • Guez, A. (2015)
    Sample-based Search Methods for Bayes-Adaptive Planning.
    Ph.D. Thesis, Gatsby Computational Neuroscience Unit, University College London.
    PDF[PDF]  BIB[BIB]
  • Guez, A. (2010)
    Adaptive control of epileptic seizures using reinforcement learning.
    M.Sc. Thesis, McGill University.
    PDF[PDF]  BIB[BIB]
Journal papers:
  • Silver, D., Huang, A., Maddison, C., Guez, A., Sifre, L., van den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., Dieleman, S., Grewe, D., Nham, J., Kalchbrenner, N., Sutskever, I., Lillicrap, T., Leach, M., Kavukcuoglu, K., Graepel, T., and Hassabis, D. (2016)
    Mastering the game of Go with deep neural networks and tree search
    Nature
    [DOI]
  • Guez, A., Silver, D., and Dayan, P. (2013)
    Scalable and Efficient Bayes-Adaptive Reinforcement Learning based on Monte-Carlo Tree Search.
    Journal of Artificial Intelligence Research (JAIR).
    PDF [PDF]  BIB[BIB] 
    [contains Bayesian reinforcement learning survey]
  • Panuccio, G.*, Guez, A.*, Vincent, R., Avoli, M., Pineau, J. (2013)
    Adaptive control of epileptiform excitability in an in vivo model of limbic seizures.
    Experimental Neurology.
    [DOI]  BIB[BIB]  (* Authors contributed equally)
  • Pineau, J., Guez, A., Vincent, R., and Avoli, M. (2009)
    Treating Epilepsy via Adaptive Neurostimulation: A Reinforcement Learning Approach.
    International Journal of Neural Systems.
    [URL]   BIB[BIB]
Conference papers:
  • Bellemare, M., Ostrovski, G., Guez, A., Thomas, P., and Munos, R. (2016)
    Increasing the Action Gap: New Operators for Reinforcement Learning.
    Proceedings of the AAAI Conference on Artificial Intelligence.
    PDF[PDF]
  • van Hasselt, H., Guez, A., Silver, D. (2016)
    Deep Reinforcement Learning with Double Q-learning.
    Proceedings of the AAAI Conference on Artificial Intelligence.
    PDF[PDF]
  • Guez, A., Heess, N., Silver, D., and Dayan, P. (2014)
    Bayes-Adaptive Simulation-based Search with Value Function Approximation.
    Advances in Neural Information Processing Systems (NIPS).
    PDF (PDF including Supp.)  
  • Guez, A., Silver, D., and Dayan, P. (2013)
    Towards a practical Bayes-optimal agent.
    The 1st Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
    [Poster]
  • Guez, A., Niyogi, R., Bach, D., Guitart-Massip, M., Dolan, R.J., Dayan, P. (2013)
    A normative theory of approach-avoidance conflicts during dynamic foraging in humans.
    The 1st Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
    [Poster]
  • Guez, A., Silver, D., and Dayan, P. (2012)
    Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search.
    Advances in Neural Information Processing Systems (NIPS).
    PDF (PDF including Supp.)   BIB[BIB]   [Videos]   [Poster]   [Code on GitHub]
    [Bayesian Reinforcement Learning, Model-based RL]
  • Guez, A. and Pineau, J. (2010)
    Multi-Tasking SLAM.
    International Conference on Robotics and Automation (ICRA).
    PDF[PDF]  BIB[BIB]  [Video]
    [Integrated exploration, POMDP, SLAM]
  • Guez, A., Vincent, R., Avoli, M. and Pineau, J. (2008)
    Adaptive Treatment of Epilepsy via Batch-mode Reinforcement Learning.
    Proceedings of the Twentieth Innovative Applications of Artificial Intelligence Conference (IAAI).
    PDF[PDF]  BIB[BIB]
    [reinforcement learning application]
Preprints:
  • Guez, A., Silver, D., and Dayan, P. (2014)
    Better Optimism By Bayes: Adaptive Planning with Rich Models.
    PDF[PDF]
Workshop papers:
  • Guez, A., Silver, D., and Dayan, P. (2012) Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search. The 10th European Workshop on Reinforcement Learning (EWRL). Edinburgh, UK.
  • Guez, A. and Pineau, J. (2009) Performing Tasks while doing Simultaneous Localization And Mapping. NIPS Workshop on Probabilistic Approaches for Robotics and Control. Whistler, Canada. PDF [poster]
  • Guez, A. and Pineau, J. (2009) Using Batch RL to Optimize Neurostimulation Strategies. Multidisciplinary Symposium on Reinforcement Learning. Montréal, Canada. PDF
  • Paduraru, C., Guez, A., Precup, D., and Pineau, J. (2009) Model-based Bayesian Reinforcement Learning with Adaptive State Aggregation. Multidisciplinary Symposium on Reinforcement Learning. Montréal, Canada. PDF
  • Bush, K., Pineau, J., Guez A., Vincent B., Panuccio G., and Avoli M. (2009) Dynamic Representations for Adaptive Neurostimulation Treatment of Epilepsy. 4th International Workshop on Seizure Prediction in Epilepsy. Kansas City, USA.
  • Vincent, R., Guez, A., Courville, A., Avoli, M., and Pineau, J. (2007) A computational model of epilepsy and response to electrical stimulation. 3rd International Workshop on Seizure Prediction in Epilepsy. Freiburg, Germany.

Teaching

Teaching Assistant - Gatsby Unit's Unsupervised Learning course
Course Webpage: http://www.gatsby.ucl.ac.uk/teaching/courses/ml1-2011.html
Teaching Assistant - Gatsby Unit's Theoretical Neuroscience course
Course Webpage: http://www.gatsby.ucl.ac.uk/~aguez/tn1/
Teaching Assistant - McGill COMP 424 (Artificial Intelligence) Winter 2010
Course Webpage: http://www.cs.mcgill.ca/~dprecup/courses/ai.html

Education and Awards

  • Ph.D., Gatsby Computational Neuroscience Unit, University College London, 2015.
  • M.Sc., McGill University, Computer Science, 2010.
  • B.Sc., McGill University, 2008. Joint Honours Mathematics and Computer Science, Cognitive Science minor. Graduated with First Class Honours.
  • NSERC Alexander Graham Bell Canada Graduate Scholarship (CGS) D, 2010-2013.
  • FQRNT Master research scholarship B1 - 2009-2010.
  • NSERC Alexander Graham Bell Canada Graduate Scholarship (CGS) M, 2008-2009.
  • CRA Outstanding Undergraduate Award, Honorable Mention, 2008.
  • NSERC Undergraduate Student Research Award (USRA), Summer 2007.


External links: