最近在看连续控制问题,看到了一个Actor-Critic算法中手动扩展features和设置linear baseline的方法,这些方法源自论文:《Benchmarking Deep Reinforcement Learning for Continuous Control》。 对于低维的features我们可以手动扩展: 代码实现: return torch.cat([observations, observations ** 2, al, al ** 2, al ** ...
In particular, we prove that actor-critic finds a globally optimal pair of actor (policy) and critic (action-value function) at a linear rate of convergence. Our analysis may serve as a preliminary step towards a complete theoretical understanding of bilevel optimization with nonconvex subproblems...
Actor-critic is a reinforcement learning method that can solve such problems through online iteration. This paper proposes an online iterative algorithm for solving linear discrete-time systems graphics games with input constraints, and this algorithm without the need for drift dynamics of agents. Each...
[15] present a actor-critic-identifier structure based on neural network (NN), and obtain the approximate Nash equilibrium of multi-player NZS differential games for nonlinear deterministic system. Ren et al. [16] use off-policy learning mechanism based on IRL technique to solve multi-player ...
" A revolutionary movement does not spread by contamination / But by resonance / Something that constitutes itself here / Resonates with the shock wave given off by something that constituted itself elsewhere / The body that resonates does so in its own way / An insurrection is not like the...
Q-learning, policy iteration and actor-critic reinforcement learning combined with metaheuristic algorithms in servo system control Facta Univ., Mech. Eng., 21 (4) (2023), pp. 615-630 CrossrefView in ScopusGoogle Scholar [31] B. Kiumarsi, F.L. Lewis, H. Modares, A. Karimpour, M.-B...
Actor-Critic Reinforcement Learning for Linear Longitudinal Output Control of a Road Vehicledoi:10.1109/itsc.2019.8917113Luca PuccettiChristian RathgeberSoren HohmannIEEEInternational Conference on Intelligent Transportation Systems
Actor-critic is a reinforcement learning method that can solve such problems through online iteration. This paper proposes an online iterative algorithm for solving linear discrete-time systems graphics games with input constraints, and this algorithm without the need for drift dynamics of agents. Each...
This paper presents a novel policy iteration approach for finding online adaptive optimal controllers for continuous-time linear systems with completely unknown system dynamics. The proposed approach employs the approximate/adaptive dynamic programming technique to iteratively solve the algebraic Riccati equation...
[22] designs the optimal control for tracking control systems by a novel HDP iteration algorithm which contains state updating, control policy iteration and performance index iteration. However, most of the above results design the optimal control for time-delay systems with known knowledge of ...