175 citations · 1.1k across the 47 of their papers we have counts for
3 papers · 1 filter
Learning to grow: control of material self-assembly using evolutionary reinforcement learning
Stephen Whitelam, Isaac Tamblyn
We show that neural networks trained by evolutionary reinforcement learning can enact efficient molecular self-assembly protocols. Presented with molecular simulation trajectories,…
Evolutionary reinforcement learning of dynamical large deviations
Stephen Whitelam, Daniel Jacobson, Isaac Tamblyn
We show how to calculate the likelihood of dynamical large deviations using evolutionary reinforcement learning. An agent, a stochastic model, propagates a continuous-time Monte Ca…
Optimizing thermodynamic trajectories using evolutionary and gradient-based reinforcement learning
Chris Beeler, Uladzimir Yahorau, Rory Coles +3
Using a model heat engine, we show that neural network-based reinforcement learning can identify thermodynamic trajectories of maximal efficiency. We consider both gradient and gra…