... allocation (MRTA) process presents itself as a combinatorial optimization (CO) problem that is usually challenging to be solved in meaningful timescales using typical (mixed)integer (non)linear programming tools. Building on a growing body of work in using graph reinforcement learning to learn search...

...Akash Agrawal; Christopher McComb Reinforcement learning algorithms can autonomously learn to search a design space for high-performance solutions. However, modern engineering often entails the use of computationally intensive simulation, which can lead to slower design timelines with highly...

...Maximilian E. Ororbia; Gordon P. Warn This article presents a framework that mathematically models optimal design synthesis as a Markov Decision Process (MDP) that is solved with reinforcement learning. In this context, the states correspond to specific design configurations, the actions correspond...

... 2019 30 03 2020 30 03 2020 01 04 2020 reinforcement learning Monte Carlo learning method machine learning workspace data-driven engineering Manufacturing is undergoing a transition to a digital phase driven by data and algorithms [ 1 , 2 ]. One enabler...