PPO | Deus Ex Machina

Protected: Value Assessment and Policy and Weaknesses in Deep Reinforcement Learning

Value assessment and strategies and weaknesses in deep reinforcement learning used for digital transformation, artificial intelligence, and machine learning tasks poor sample efficiency, difficulty in validating methods as well, impact of implementation practices on performance, library initial values, poor reproducibility, over-training, local optimum, dexterity, TRPO, PPO, continuous value control, image control, policy-based, value-based

2023.03.30

アルゴリズム:Algorithmsグラフ理論スパースモデリング幾何学:Geometry強化学習微分積分:Calculus最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: TRPO/PPO and DPG/DDPG, an improvement of the Policy Gradient method of reinforcement learning

TRPO/PPO and DPG/DDPG (Pendulum, Actor Critic, SequentialMemory, SequentialMemory, and SequentialMemory), which are improvements of Policy Gradient methods of reinforcement learning used for digital transformation, artificial intelligence, and machine learning tasks. Adam, keras-rl, TD error, Deep Deterministic Policy Gradient, Deterministic Policy Gradient, Advanced Actor Critic, A2C, A3C, Proximal Policy Optimization, Trust Region Policy Optimization, Python)

2023.03.16