no code implementations • 21 Nov 2017 • Ashley D. Edwards, Charles L. Isbell Jr
A major bottleneck for developing general reinforcement learning agents is determining rewards that will yield desirable behaviors under various circumstances.
General Reinforcement Learning Generative Adversarial Network +2
no code implementations • 25 May 2017 • Ashley D. Edwards, Srijan Sood, Charles L. Isbell Jr
One problem with this approach is that we typically need to redefine the rewards each time the goal changes, which often requires some understanding of the solution in the agents environment.