Overview

Starter Kit <>

RL4Ising applies reinforcement learning algorithms to the task of finding the ground state of the Ising model. Recent advances in RL allow for more efficient searching of huge discrete spaces and the growth of community support in problems of combinatorial optimization.

Tasks

We organize two tasks to promote the Ising model:

1. RL4MaxCut.

   Develop RL algorithms to solve the MaxCut problem using provided graphs.

2. RL4Ising

   Develop RL algorithms to find ground states of Ising models using provided instances.

References