python a3c_main.py --num-processes 16 --map-size 7 --max-episode-length 30 --dump-location ./saved/ --test-data ./test_data/m7_n1000.npy

python a3c_main.py --num-processes 0 --evaluate 1 --map-size 7 --max-episode-length 30 --load ./saved/model_best --test-data ./test_data/m7_n1000.npy

python a3c_main.py --num-processes 0 --evaluate 1 --map-size 15 --max-episode-length 40 --load ./pretrained_models/m15_l40 --test-data ./test_data/m15_n1000.npy

python generate_test_data.py --map-size 7 --num-mazes 100 --test-data-location ./test_data/ --test-data-filename my_new_test_data.npy

  -h, --help            show this help message and exit
  -l L, --max-episode-length L
                        maximum length of an episode (default: 30)
  -m MAP_SIZE, --map-size MAP_SIZE
                        m: Size of the maze m x m (default: 7), must be an odd
                        natural number
  --lr LR               learning rate (default: 0.001)
  --num-iters NS        number of training iterations per training thread
                        (default: 10000000)
  --gamma G             discount factor for rewards (default: 0.99)
  --tau T               parameter for GAE (default: 1.00)
  --seed S              random seed (default: 1)
  -n N, --num-processes N
                        how many training processes to use (default: 8)
  --num-steps NS        number of forward steps in A3C (default: 20)
  --hist-size HIST_SIZE
                        action history size (default: 5)
  --load LOAD           model path to load, 0 to not reload (default: 0)
  -e EVALUATE, --evaluate EVALUATE
                        0:Train, 1:Evaluate on test data (default: 0)
  -d DUMP_LOCATION, --dump-location DUMP_LOCATION
                        path to dump models and log (default: ./saved/)
  -td TEST_DATA, --test-data TEST_DATA
                        Test data filepath (default: ./test_data/m7_n1000.npy)

@inproceedings{chaplot2018active,
  title={Active Neural Localization},
  author={Chaplot, Devendra Singh and Parisotto, Emilio and Salakhutdinov, Ruslan},
  booktitle={International Conference on Learning Representations},
  year={2018}
}