reward model

A reward model is a component of a reinforcement learning system that defines the objective function or reward function. The reward function quantifies how well an agent performs a task, and it is used to guide the agent's decision-making process. The objective of the agent is to maximize the cumulative reward over time by selecting actions that lead to higher reward. The reward model is designed to provide positive rewards for desirable outcomes and negative rewards for undesirable outcomes. In reinforcement learning, the reward model is typically specified by the designer, and the agent learns to maximize the reward through trial and error.

相关问题

# 训练模型 model.learn(total_timesteps=hyperparams['total_timesteps'], callback=callbacks, reward_fn=reward_function) # 关闭环境 env.close() Traceback (most recent call last): File "D:\ruanjian\xzq\强化学习\超级马里奥3.py", line 86, in <module> model.learn(total_timesteps=hyperparams['total_timesteps'], callback=callbacks, reward_fn=reward_function) TypeError: learn() got an unexpected keyword argument 'reward_fn'

这个错误提示表明，`learn()`函数不支持`reward_fn`参数。这可能是因为你使用的是某个特定版本的强化学习库，而这个版本的库中没有`reward_fn`参数。你可以查阅该库的文档，了解该版本库中`learn()`函数的参数列表，以确定正确的参数名称和用法。或者你可以尝试升级该库的版本，看看是否支持`reward_fn`参数。

model.learn(total_timesteps=hyperparams['total_timesteps'], callback=callbacks, reward_fn=reward_function)这一行代码哪里有问题

这一行代码的问题可能在于参数`reward_fn=reward_function`。`reward_function`需要是一个函数，这个函数用于计算智能体在每个时间步上的奖励值。如果没有定义`reward_function`，或者`reward_function`不是一个函数类型，那么这个参数将会引发错误。你需要确保这个参数传递的是一个可调用的函数。