READEME.md

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.Array2D(),
    "actions":datasets.Array2D(),
    "hidden_state":datasets.Array2D(),
}

Data Fields

• obs: An Array2D containing observations from 8 trajectories of an evaluated agent.
• actions: An Array2D containing actions from 8 trajectories of an evaluated agent.
• hidden_state: An Array2D containing corresponding hidden states generated by EfficientZero, from 8 trajectories of an evaluated agent.

Data Splits

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