config.yaml 1.8 KB

12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758
  1. general:
  2. experiment_tag: 'lstm_drqn_'
  3. env_id: 'twcc_easy_level10_gamesize100_step50_seed9_train'
  4. run_test: True
  5. valid_env_id: 'twcc_easy_level10_gamesize10_step50_seed9_validation'
  6. test_env_id: ['twcc_easy_level5_gamesize10_step50_seed1_test',
  7. 'twcc_easy_level10_gamesize10_step50_seed0_test',
  8. 'twcc_easy_level15_gamesize10_step50_seed3_test',
  9. 'twcc_easy_level20_gamesize10_step50_seed2_test',
  10. 'twcc_easy_level30_gamesize10_step50_seed3_test']
  11. # test_env_id: ['twcc_easy_level10_gamesize10_step50_seed0_test']
  12. discount_gamma: 0.5
  13. random_seed: 42
  14. observation_cache_capacity: 1 # concat window of history observation, 1 means no history observations available
  15. experiments_dir: 'experiments/lstm_drqn'
  16. use_cuda: True # disable this when running on machine without cuda
  17. provide_prev_action: True
  18. num_grids: 25
  19. margin: 3
  20. # replay memory
  21. history_size: 8
  22. update_from: 4
  23. replay_memory_capacity: 500000
  24. replay_memory_priority_fraction: 0.25 # 0.0 to disable this
  25. update_per_k_game_steps: 4
  26. replay_batch_size: 32
  27. # epsilon greedy
  28. epsilon_anneal_epochs: 1000 # -1 if not annealing
  29. epsilon_anneal_from: 1.0
  30. epsilon_anneal_to: 0.2
  31. # counting reward
  32. revisit_counting: True
  33. revisit_counting_lambda_anneal_from: 1.0
  34. revisit_counting_lambda_anneal_epochs: -1 # -1 if not annealing
  35. revisit_counting_lambda_anneal_to: 0.0
  36. training:
  37. scheduling:
  38. batch_size: 10
  39. test_batch_size: 10
  40. epoch: 3000
  41. model_checkpoint_path: 'saved_models/model1.pt'
  42. logging_frequency: 20
  43. optimizer:
  44. step_rule: 'adam' # adam, sgd
  45. learning_rate: 0.001
  46. clip_grad_norm: 5
  47. model:
  48. lstm_dqn:
  49. embedding_size: 20
  50. encoder_rnn_hidden_size: [100]
  51. action_scorer_hidden_dim: 64
  52. dropout_between_rnn_layers: 0.