silverjoda / nexabots Public

Notifications You must be signed in to change notification settings
Fork 1
Star 7

Repo for hexapod expert policy multiplexer journal paper.

7 stars 1 fork Branches Tags Activity

Name		Name	Last commit message	Last commit date
Latest commit History 494 Commits
.idea		.idea
src		src
README.md		README.md

Repository files navigation

Nexabots

To run an example environment with given terrain type:

Add src and project directory to pythonpath

export PYTHONPATH="${PYTHONPATH}:/absolute_dir_to_project/nexabots/"
export PYTHONPATH="${PYTHONPATH}:/absolute_dir_to_project/nexabots/src"

Navigate to environment

cd src/envs/locom_benchmarks/hex_locomotion  (or quad_locomotion, or snake_locomotion)

Run demo example.

python hex_blind.py --terrain perlin

Gives the list of available terrains for generation methods #1 and #2.

python quad_blind.py --help

To run a reinforcement learning example with any evironment navigate to and run policy gradient algorithm on environment of your choice (you can set it in the script). Any custom environments should work if they implement the step and reset methods similarly as to OpenAI Gym

cd nexabots/src/algos/PG

python pg.py