google-deepmind / google-deepmind/dm_control

Reward is always 0 in Hopper

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描述

In Hopper, reward is always 0 independent of the action. The problem is that this code which is used in reward calculation in hopper.py get_reward(self, physics) function, always return 0 as the value of standing:
`standing = rewards.tolerance(physics.height(), (_STAND_HEIGHT, 2))`

When I check `env._physics.height()` after environment reset, I saw that the height is initialized as a negative value always. Therefore it is impossible for this code fragment `rewards.tolerance(physics.height(), (_STAND_HEIGHT, 2))` to return 1, since _STAND_HEIGHT is defined as 0.6 for Hopper.

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调研方向

从 hopper.py 中的 get_reward(self, physics) 开始,检查重置高度以及 rewards.tolerance 和 _STAND_HEIGHT。复现报告的重置后奖励为零的问题,确定站立状态为何仍为零,并验证修复后奖励会对动作作出适当响应。

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评估

技术栈
python
领域
machine-learning
Issue 类型
缺陷
难度
3/5
预计耗时
1-2 天
活跃度
停滞
描述清晰度
基本清楚
新手友好度
38/100

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