1
0
Fork 0
mirror of https://gitlab.rlp.net/mobitar/ReCo.jl.git synced 2024-11-08 22:21:08 +00:00

Further RL documentation

This commit is contained in:
Mo8it 2022-02-07 18:41:34 +01:00
parent 146b024e19
commit 51c9b0b72f

View file

@ -72,16 +72,57 @@ Import the package:
using ReCo using ReCo
---- ----
Run a reinforcement learning process and return the environment helper: Run a reinforcement learning process and return the environment helper and the the path of the process directory relative to the directory `ReCo.jl`:
[source, julia] [source, julia]
---- ----
env_helper = run_rl(ENVTYPE) env_helper, rl_dir = run_rl(ENVTYPE)
---- ----
ENVTYPE has to be replaced by one of the environments named after the file names in the directory `ReCo.jl/RL/Envs`, for example: `LocalCOMEnv`. A description of an environment is included at the beginning of the corresponding file. ENVTYPE has to be replaced by one of the environments named after the file names in the directory `ReCo.jl/RL/Envs`, for example: `LocalCOMEnv`. A description of an environment is included at the beginning of the corresponding file.
For more information about all possible optional arguments, press `?` in the REPL after running `using ReCo`. Then type `run_rl` followed by pressing enter. For more information about all possible optional arguments, press `?` in the REPL after running `using ReCo`. Then type `run_rl` followed by pressing enter.
`env_helper` has the abstract type `EnvHelper`. To access the Q-matrix, enter the following:
[source, julia]
----
env_helper.shared.agent.policy.learner.approximator.table
----
To generate a LaTeX table with the states and actions combintation names for the Q-matrix, run the follwing:
[source, julia]
----
include("src/RL/latex_table.jl")
latex_rl_table(env_helper, FILENAME)
----
FILENAME has to be replaced by the wanted file name of the `.tex` file. This file can then be found under `ReCo.jl/exports/FILENAME`.
To access the rewards, run the following:
[source, julia]
----
env_helper.shared.hook.rewards
----
To plot the rewards, run the following:
[source, julia]
----
plot_rewards(rl_dir)
----
To plot the mean of kappa as the ratio of the eigenvalues of the gyration tensor, run the following:
[source, julia]
----
include("analysis/mean_kappa.jl")
plot_mean_kappa(; rl_dir=rl_dir, n_last_episodes=N_LAST_EPISODES)
----
`N_LAST_EPISODES` is the number of the last episodes of the learning process to average over.
== Run analysis == Run analysis
After running the following command blocks in the REPL, the output can be found in the directory `exports/graphics`. After running the following command blocks in the REPL, the output can be found in the directory `exports/graphics`.