20240409 deep reinforcement learning, Unity Reacher v2, env solved

Опубликовано: 17 Май 2026
на канале: Wenjing Liu
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#machinelearning #reinforcementlearning

✅ Result: A DDPG model was trained in one Unity-Reacher-v2 environment with 1 agent (1 robot arm) for 155 episodes, then evaluated in 3 environments (each with 1 agent) parallelly for 150 consecutive episodes and got an average score of 33.92(0.26) (0.26 is the standard standard deviation of scores in different envs). also the trained model is tested to control 20 agents in 4 envs parallelly and got a score of 34.24(0.10).

https://github.com/nov05/udacity-deep...