17、利用Python进行Unity模拟环境的定制训练与参数调优

利用Python进行Unity模拟环境的定制训练与参数调优

1. Python在Unity模拟环境中的基础操作

1.1 生成动作与模拟推进

在Unity模拟环境中，我们可以使用Python代码来控制智能体的行为。以下是一段示例代码，展示了如何为所有智能体生成动作、设置动作、推进模拟并获取新的模拟结果：

# Generate an action for all agents
action = spec.action_spec.random_action(len(decision_steps))
# Set the actions
env.set_actions(behavior, action)
# Move the simulation forward
env.step()
# Get the new simulation results
decision_steps, terminal_steps = env.get_steps(behavior)
if tracked_agent in decision_steps: # The agent requested a decision
    episode_rewards += decision_steps[tracked_agent].reward
if tracked_agent in terminal_steps: # Agent terminated its episode
    episode_rewards += terminal_steps[tracked_agent].reward
    done = True
print(f"Total r