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This repository has been archived by the owner on May 21, 2022. It is now read-only.
using OpenAIGym
function run_env(env_name, n_episodes)
println("Run $n_episodes of $env_name")
env = GymEnv(env_name)
for i ∈ 1:n_episodes
T = 0
R = run_episode(env, RandomPolicy()) do (s, a, r, s′)
render(env)
T += 1
end
@info("Episode $i finished after $T steps. Total reward: $R")
end
close(env)
end
env_names = ["procgen:procgen-$stub-v0" for stub in ["bigfish","bossfight","caveflyer","chaser","climber","coinrun","dodgeball","fruitbot",
"heist","jumper","leaper","maze","miner","ninja","plunder","starpilot"]]
get_env_name() = env_names[rand(1:length(env_names))]
function run_envs(n_envs, n_episodes)
println("Run $n_envs procgen envs")
for i ∈ 1:n_envs
T = 0
env_name = get_env_name()
run_env(env_name, n_episodes)
end
end
How could we add the DeepMind BSuite envs?
They have a wrapper for OpenAI Gym: https://github.com/deepmind/bsuite#using-bsuite-in-openai-gym-format
Got ProcGen to work if anyone wants it:
I also have custom envs for molecular dynamics, NLP, causality, [self]supervised learning, etc if anyone wants them
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