bitrl & cuberl Documentation
Simulation engine for reinforcement learning agents
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play.py File Reference

Namespaces

namespace  play
 

Functions

dict play.load_policy (Path filename)
 

Variables

 play.policy_path = Path('/home/alex/qi3/cuberl/build/examples/rl/rl_example_10/policy.csv')
 
dict play.policy = load_policy(policy_path)
 
int play.max_episode_steps = 200
 
str play.version = 'v0'
 
str play.env_tag = f"CliffWalking-{version}"
 
 play.env
 
 play.state = observation
 
 play._
 
bool play.done = False
 
int play.total_reward = 0
 
dict play.action = policy[state]
 
 play.observation
 
 play.reward
 
 play.truncated
 
 play.info