AI3SD Video: Reinforcement Learning Methods
AI3SD Video: Reinforcement Learning Methods
Reinforcement learning is a machine learning paradigm in which an agent learns to make decisions to achieve a long-term goal. In the past five years, the previously somewhat niche method has seen substantially increased interest from within the chemistry community, driven by the need for a machine learning approach to problems of planning and sequential decision making and recent developments in harnessing the power of neural networks to make reinforcement learning achievable for large problems. This talk will introduce the theory that underpins reinforcement learning, review its applications in chemistry to date with a particular focus on the field of drug discovery and molecular design, and consider the future of this still-developing approach.
Gow, Stephen
922171a1-6d31-4969-9e2e-8443daff9c0c
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
1 March 2022
Gow, Stephen
922171a1-6d31-4969-9e2e-8443daff9c0c
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Gow, Stephen
(2022)
AI3SD Video: Reinforcement Learning Methods.
Frey, Jeremy G., Kanza, Samantha and Niranjan, Mahesan
(eds.)
AI4SD Network+ Conference, Chilworth Manor , Southampton, United Kingdom.
01 - 03 Mar 2022.
(doi:10.5258/SOTON/AI3SD0191).
Record type:
Conference or Workshop Item
(Other)
Abstract
Reinforcement learning is a machine learning paradigm in which an agent learns to make decisions to achieve a long-term goal. In the past five years, the previously somewhat niche method has seen substantially increased interest from within the chemistry community, driven by the need for a machine learning approach to problems of planning and sequential decision making and recent developments in harnessing the power of neural networks to make reinforcement learning achievable for large problems. This talk will introduce the theory that underpins reinforcement learning, review its applications in chemistry to date with a particular focus on the field of drug discovery and molecular design, and consider the future of this still-developing approach.
Video
ai4sd_march_2022_day_1_StephenGow
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Published date: 1 March 2022
Additional Information:
Stephen Gow arrived at the University of Southampton as a mathematics and statistics student in 2011, graduating in 2014 and completing a PhD in computational modelling in 2020. After a short spell as a Knowledge Transfer Partnership Associate in Machine Learning, Semantic Web & Voice Automation Technologies, he is now a researcher working on projects including the application of machine learning in chemistry and estimation of population characteristics of refugee populations.
Venue - Dates:
AI4SD Network+ Conference, Chilworth Manor , Southampton, United Kingdom, 2022-03-01 - 2022-03-03
Identifiers
Local EPrints ID: 468632
URI: http://eprints.soton.ac.uk/id/eprint/468632
PURE UUID: a36dc0e5-8fbc-4941-84c9-304eff9efe8a
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Date deposited: 19 Aug 2022 16:33
Last modified: 17 Mar 2024 04:01
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Editor:
Mahesan Niranjan
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