More engineers are turning to reinforcement learning to incorporate adaptive and self-tuning control into industrial systems. It aims to strike a balance between traditional ...
In this talk I will discuss first solutions to some of the challenges we face in developing online reinforcement learning (RL) algorithms for use in digital health interventions targeting patients ...
Progress in self-driving cars and other forms of automation will slow dramatically unless machines can hone skills through experience. Inside a simple computer simulation, a group of self-driving ...
Multi-Objective Reinforcement Learning (MORL) is an emerging field that extends the conventional reinforcement learning paradigm by enabling agents to optimise multiple conflicting objectives ...
Nearly a century ago, psychologist B.F. Skinner pioneered a controversial school of thought, behaviorism, to explain human and animal behavior. Behaviorism directly inspired modern reinforcement ...
The various cutting-edge technologies that are under the umbrella of artificial intelligence are getting a lot of attention lately. As the amount of data we generate continues to grow to mind-boggling ...
This course is available on the MPA in Data Science for Public Policy, MSc in Applied Social Data Science, MSc in Data Science, MSc in Geographic Data Science, MSc in Health Data Science, MSc in ...
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