HighJax/CITATION.cff at master · HumanCompatibleAI/HighJax · GitHub

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cff-version: 1.2.0
message: If you use HighJax in your research, please cite the BXRL paper.
title: HighJax
abstract: >-
  HighJax is an autonomous driving environment for Reinforcement Learning
  research, a JAX implementation of HighwayEnv. It includes Octane, a Rust-based
  TUI for examining experiment runs.
type: software
authors:
  - family-names: Rachum
    given-names: Ram
    email: ram@rachum.com
    affiliation: University of California, Berkeley
repository-code: https://github.com/HumanCompatibleAI/HighJax
url: https://github.com/HumanCompatibleAI/HighJax
license: MIT
version: 0.1.0
keywords:
  - reinforcement-learning
  - jax
  - autonomous-driving
  - explainable-ai
preferred-citation:
  type: conference-paper
  title: 'BXRL: Behavior-Explainable Reinforcement Learning'
  authors:
    - family-names: Rachum
      given-names: Ram
    - family-names: Amitai
      given-names: Yotam
    - family-names: Nakar
      given-names: Yonatan
    - family-names: Mirsky
      given-names: Reuth
    - family-names: Allen
      given-names: Cameron
  year: 2026
  collection-title: >-
    Proceedings of the Workshop on Explainable Artificial Intelligence (XAI) at
    IJCAI-ECAI 2026
  conference:
    name: >-
      Workshop on Explainable Artificial Intelligence (XAI) at IJCAI-ECAI 2026
    city: Bremen
    country: DE
    date-start: '2026-08-15'
    date-end: '2026-08-16'
  url: https://arxiv.org/abs/2603.23738
  identifiers:
    - type: other
      value: arXiv:2603.23738
      description: arXiv preprint