README.md

metadata

license: apache-2.0

Dataset Card for Pong-v4-expert-MCTS

Table of Contents

• Dataset Description
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits

Dataset Description

This dataset includes 8 episodes of pong-v4 environment. The expert policy is EfficientZero, which is able to generate MCTS hidden states.

Dataset Structure

Data Instances

A data point comprises tuples of sequences of (observations, actions, hidden_states):

{
    "obs":datasets.Array3D(),
    "actions":int,
    "hidden_state":datasets.Array3D(),
}

Data Fields

• obs: An Array3D containing observations from 8 trajectories of an evaluated agent. The data type is uint8 and each value is in 0 to 255.
• actions: An integer containing actions from 8 trajectories of an evaluated agent. This value is from 0 to 5.
• hidden_state: An Array3D containing corresponding hidden states generated by EfficientZero, from 8 trajectories of an evaluated agent. The data type is float32.

Data Splits

There is only a training set for this dataset, as evaluation is undertaken by interacting with a simulator.