N-step-Dueling-DDQN-PER-Pacman Using N-step dueling DDQN with PER for learning how to play a Pacman game SummaryDeepMind published its famous paper Playing Atari with Deep Reinforcement Learning, in which a new algorithm called DQN was implemented. It showed that an AI agent could learn to...
sum() total_reward += reward obs = next_obs if done: break loss_per_reward = total_loss/(total_loss_reward if total_loss_reward else 1) return total_reward,loss_per_reward def run_evaluate_epoches(agent, env, epoches=5, render=False): # 评估agent eval_reward = [] for episode ...
深度强化学习量化交易——实现从单资产DDQN到多资产DDPG 这两周开始学习深度强化学习算法交易,上周基于pytorch先是做了一个单资产的DDQN交易框架,这周又将原任务拓展到了多资产连续动作空间的设定。本文将基于这两个任务设定,从代码层面给出完整的任务设定以及pytorch框架。食用前请看说明: 本文假设读者已经有基本的MDP...
if current_time - last_graph_update_time > timedelta(seconds=10): self.save_graph(rewards_per_episode, epsilon_history) last_graph_update_time = current_time # 如果积累了足够的经验,则进行训练 if len(memory) > self.mini_batch_size: mini_batch = memory.sample(self.mini_batch_size) self....
Tracks difficulty scores per client Updates smoothly (90/10 split) Combines difficulty with performance for aggregation weights The interaction works like this: RL agent observes state (loss history) Selects components to activate Clients train with selected components ...
The implement of all kinds of dqn reinforcement learning with Pytorch pytorchdqnddqndueling-dqniqncategorical-dqnsoft-q-learningrainbow-dqnqr-dqnprioritized-dqnnoisy-dqnn-step-dqnfqfdistributional-dqnmmddqn UpdatedMar 25, 2021 Python FelipeMarcelino/2048-Gym ...
Both can be enhanced withNoisy layer,Per(Prioritized Experience Replay),Multistep Targetsand be trained in aCategorical version (C51). Combining all these add-ons will lead to thestate-of-the-artAlgorithm of value-based methods called:Rainbow. ...
Path planning is a key technology for Unmanned Aerial Vehicles (UAVs) to complete the operational mission in a complex battlefield environment. A step-by-step path planning method based on the Layered Double Deep Q-Network with Prioritized Experience Replay (Layered PER-DDQN) is proposed in this...
本文从网络结构上入手,对现有的算法包括DQN、Double DQN以及PER算法进行了改进。 2. 算法原理和过程 文中第一章就直接向我们展示了提出的“dueling architecture”结构,如图所示: 图中将原有的DQN算法的网络输出分成了两部分:即值函数和优势函数共同组成,在数学上表示为: Q(s, a ; \theta, \alpha, \beta)...
Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL) - Replace DDQN with Duel DDQN · collapse-del/DRL-Pytorch@3de46db