2009. Natural Actor-Critic Algorithms. Automatica 45(11):2471-2482.S. Bhatnagar, R. Sutton, M. Ghavamzadeh, and M. Lee. Natural actor-critic algorithms. Automatica, 45(11): 2471-2482, 2009.S. Bhatnagar, R. S. Sutton, M. Ghavamzadeh, and M. Lee. Natural actor-critic algorithms. ...
https://homes.cs.washington.edu/~todorov/courses/amath579/reading/NaturalActorCritic.pdfhomes.cs.washington.edu/~todorov/courses/amath579/reading/NaturalActorCritic.pdf 在求解优化问题时,一个很常见的做法就是用最速梯度下降法 △θ=−η∇θL(θ) 传统监督学习会按照这种方式去更新模型参数,在最...
1. Introduction Natural actor-critics are an increasingly popular class of algorithms for ?nding locally optimal policies for continuous-action Markov decision processes (MDPs). We show that the existing discounted natural actor-critic algorithms (Degris et al., 2012; Peters & Schaal, 2006; 2008...
We show that several popular discounted reward natural actor-critics, including the popular NAC-LSTD and eNAC algorithms, do not generate unbiased estimates of the natural policy gradient as claimed. We derive the first unbiased discounted reward natural actor-critics using batch and iterative approache...
We show that several well-known reinforcement learning methods such as the original Actor-Critic and Bradtke's Linear Quadratic Q-Learning are in fact Natural Actor-Critic algorithms. Empirical evaluations illustrate the effectiveness of our techniques in comparison to previous methods, and also ...
The existing natural gradient-based actor-critic algorithms with convergence guarantees require fixed features for approximating both policy and value functions. This often leads to sub-optimal learning in many RL applications. On the other hand, our proposed algorithm utilizes compatible features that ...
Lee, `Incremental Natural Actor-Critic Algorithms', in NIPS, (2008).Bhatnagar, S., Sutton, R.S., Ghavamzadeh, M., Lee, M.: Incremental natural actor-critic algorithms. In: Advances in NIPS, vol. 21 (2008)Bhatnagar, S., Sutton, R. S., Ghavamzadeh, M., and Lee, M. (2008)...
A recursive least-square filter-based episodic natural actor-critic algorithm is used to find the optimal impedance parameters. The effectiveness of the proposed method was tested through dynamic simulations of various contact tasks. The simulation results demonstrated that the proposed method optimizes ...
We show that several well-known reinforcement learning methods such as the original Actor-Critic and Bradtke's Linear Quadratic Q-Learning are in fact Natural Actor-Critic algorithms. Empirical evaluations illustrate the effectiveness of our techniques in comparison to previous methods, and also ...
V. NATURAL GRADIENT ACTOR-CRITIC ALGORITHMS The natural gradient clearly performs better as it always finds the optimal point, whereas the standard gradient generates paths that are leading to points in the space which are not even feasible, because of the radius which needs to be positive. ...