Abstract:
Here the Newton's Method direct action selection approach to continuous action-space reinforcement learning is extended to use an eligibility trace. This is then compared...Show MoreMetadata
Abstract:
Here the Newton's Method direct action selection approach to continuous action-space reinforcement learning is extended to use an eligibility trace. This is then compared to the momentum term approach from the literature in terms of the update equations and also the success rate and number of trials required to train on two variants of the simulated Cart-Pole benchmark problem. The eligibility trace approach achieves a higher success rate with a far wider range of parameter values than the momentum approach and also trains in fewer trials on the Cart-Pole problem.
Date of Conference: 27-29 September 2017
Date Added to IEEE Xplore: 09 November 2017
ISBN Information: