Published October 23, 2025 | Version v1
Software Open

Code for the AB-HSVI algorithm and the experiments in the paper: "Multi-Environment POMDPs: Discrete Model Uncertainty Under Partial Observability" (NeurIPS 2025)

Creators

  • 1. ROR icon Radboud University Nijmegen
  • 2. ROR icon The University of Texas at Austin
  • 3. ROR icon University of Antwerp
  • 4. ROR icon Ruhr University Bochum

Description

This repository contains code to run the experiments in the paper Multi-Environment POMDPs: Discrete Model Uncertainty Under Partial Observability.

For future reference and potential updates to AB-HSVI, please refer to the GitHub repository used (https://github.com/ai-fm/Code-for-Multi-Environment-POMDPs-Discrete-Model-Uncertainty-Under-Partial-Observability).

Files

AB-HSVI_NeurIPS_2025.zip

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Additional details

Funding

European Commission
DEUCE - Data-Driven Verification and Learning Under Uncertainty 101077178
United States Air Force Office of Scientific Research
FA9550-22-1-0403
Office of Naval Research
N00014-24-1-2797
Research Foundation - Flanders
SynthEx G0AH524N