czlwang / ltl-environment-dev

LTL Environment Dev

Environment grid world for Encoding formulas as deep networks: Reinforcement learning for zero-shot execution of LTL formulas, based on the Craft-world from Andreas et al. (2017)

Structure

• algo/ contains the code to train a model using Advantage Actor Critic
• language/ contains the code to generate a dataset of (sentence, formula, environment) examples
  • usage: language/dataset.py --n_sentence 10 --dataset_path examples_out
• worlds/craft_world.py contains all the rules of the craft world environment as well as it's GUI
  • usage: worlds/craft_world.py to obtain an GUI
• spot2ba.py contains the hooks into Spot needed to maintain the FSA
• ltl2tree.py contains the code that specifies the tree structure of the planner model. This tree is formed according to the parse of the given LTL formula.