Repository implements a SMILES-based reinforcement learning framework to quantify visual complexity of organic molecules. It extracts molecular descriptors via RDKit, trains an RL agent to rank ...

The particular attractiveness of reinforcement learning is that it teaches systems to focus on the long-term reward – win the game – rather than just predict the current best move, without considering ...

The automatic generation of power grid flow diagrams is one of the important research topics in the field of power grid operations. Reinforcement learning is commonly used to describe and solve the ...

Implementation of the paper "Improving Variable Orderings of Approximate Decision Diagrams using Reinforcement Learning". A challenge in the design of scalable algorithms is the efficient computation ...

In this paper, we propose a reinforcement learning (RL)-based decision algorithm to build the optimal hierarchical prediction structure under a random-access configuration (RA-HPS) in Versatile Video ...