To make a reinforcement learning program for protein design, the scientists gave the computer millions of simple starting molecules. The software then made ten thousand attempts at randomly ...

Tensorforce is an open-source deep reinforcement learning framework, with an emphasis on modularized flexible library design and straightforward usability for applications in research and practice.

Metaheuristic algorithms have been investigated intensively to address highly complex combinatorial optimization problems. However, most metaheuristic algorithms have been designed manually by ...

Parallel Reinforcement Learning: A Framework and Case Study. IEEE/CAA Journal of Automatica Sinica. Abstract: Notes: Last updated on 10/21/2018. University of Waterloo. University of Waterloo.

Enables seamless data exchange between state-of-the-art Multi-Agent reinforcement learning framework Ray RLlib and ns-3 Supports the simulation of NR-U and its LBT channel access mechanism Facilitates ...

The reinforcement learning problem in AI is how to design agents that achieve their goals by perceiving and acting in their environments. Reinforcement learning ... problem-solving framework.

Training AI-driven design systems that generalize across chips is challenging because it requires learning to optimize the placement of all possible chip netlists onto all possible canvases.