Fast Reinforcement Learning After Pretraining

This article is available here as a jupyter notebook. We presented at IJCNN, 2015 the following paper, which won the Best Paper Award Anderson, C., Lee, M., and Elliott, D., “Faster Reinforcement Learning After Pretraining Deep Networks to Predict State Dynamics“, Proceedings of the IJCNN, 2015, Killarney, Ireland. Abstract: Deep learning algorithms have recently appeared … Read more

Mountain Car Solved with Reinforcement Learning in Matlab

Problems whose solutions optimize an objective function defined over multiple steps generally require considerable a prior knowledge. Dynamic programming techniques are able to solve such multi-stage, sequential decision problems, but they require complete knowledge of the state space, including state transition probabilities. Bertsekas (1995) has recently published a two-volume text that covers current dynamic programming … Read more