Project structure of: openai/Video-Pre-Training
agent.py
Configure Minecraft agent for reinforcement learningbehavioural_cloning.py
Trains actor-critic model for behavioral cloning.data_loader.py
Data loader for batch processing with worker threadsinverse_dynamics_model.py
Minecraft action predictor with IDM model.action_head.py
ActionHead: Reinforcement learning action heads abstract base classaction_mapping.py
Action mapping for video game inputs and management.actions.py
Minecraft actions, quantization, and transformer.impala_cnn.py
ImpalaCNN: Customizable, Multi-Stack Classification Modelmasked_attention.py
Masked Attention for time series data.minecraft_util.py
Compute entropy from categorical head outputs.misc.py
Data processing tasks and function design discussed.mlp.py
MLP class: Neural network with specified layers, normed linear.normalize_ewma.py
Normalizes data, maintains running mean & variance.policy.py
MinecraftAgentPolicy with reinforcement learning, image preprocessingscaled_mse_head.py
Scaled MSE head for linear output layer and MSE loss.torch_util.py
Torch utilities: libraries, device defaults, tensor functions.tree_util.py
PyTree API utility functions and data type registration.util.py
Neural network utilities for data processingxf.py
Attention mechanism, layers for transformer models.
README.md
Minecraft AI training, competition, resource data, 10-min house building.requirements.txt
Installs essential libraries for Python.run_agent.py
Run MineRL model with pre-trained weights.run_inverse_dynamics_model.py
Inverse dynamics model with game inputs and video streaming.