/neural-physics

Probabilistic Neural Physics Engine ⚽

Primary LanguageJupyter Notebook

Neural Probablistic Physics

Attempt to be sample efficient in learning intuitive physics by treating the environment as a playground. Our uncertainty based approach learns 5x faster than vanilla SGD.

Here are a few results from the trained model.

Our model is probablistic, here are examples of a few rollouts,

Running

Pre-Trained Model Zoo

This repository has a recreation of Chang et. al.'s neural physics engine, as well as our probablistic neural physics engine. The main driver file is npe_main.py.

Generate and train as,

python npe_main.py --gen_data --dataset PATH_TO_DATASET
python npe_main.py --train --dataset PATH_TO_DATASET --model PATH_TO_MODEL
python npe_main.py --model_simulation --model PATH_TO_MODEL

Of course, one can also just show the actual chipmunk simulation,

python npe_main.py --show_world

Cleaning

Just as a word of warning, this repo is still in the process of being cleaned.