Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Zero-Knowledge Proofs for Classical Planning Problems
Authors: Augusto B. Corrêa, Clemens Büchner, Remo Christen
AAAI 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We show a zero-knowledge protocol (Goldwasser, Micali, and Rackoff 1985) for proving plan existence. The protocol is interactive and probabilistic. (...) We now introduce our protocol, ZK-BOUNDEDPLANEX. (...) We first analyze the completeness and soundness of our protocol. (...) We now prove that the ZK-BOUNDEDPLANEX protocol is zero-knowledge. |
| Researcher Affiliation | Academia | Augusto B. Corrˆea, Clemens B uchner, Remo Christen University of Basel, Switzerland EMAIL |
| Pseudocode | Yes | ZK-BOUNDEDPLANEX: Step-by-Step We formalize each step of our protocol next. A concrete example is available as a technical report (Corrˆea, B uchner, and Christen 2022). Step 0. P and V have as common input Π, k , where Π = V, A, I, G and k O( Π c) for some constant c N. The prover P claims to know a plan π for Π with |π| k. Step 1. P transforms Π into some new task ˆΠ so it is computationally hard for V to correctly identify actions and variables. (...) |
| Open Source Code | No | The paper does not provide any concrete access information (e.g., specific repository link, explicit code release statement) for source code. |
| Open Datasets | No | The paper describes a theoretical protocol and does not use datasets for training or evaluation purposes, nor does it provide access information for any such datasets. |
| Dataset Splits | No | The paper describes a theoretical protocol and does not use datasets with training/validation/test splits. Therefore, no split information is provided. |
| Hardware Specification | No | The paper is theoretical and does not report on experiments, thus no hardware specifications are mentioned. |
| Software Dependencies | No | The paper describes a theoretical protocol and does not mention specific software dependencies with version numbers needed for replication. |
| Experiment Setup | No | The paper describes a theoretical protocol and does not provide details on an experimental setup, hyperparameters, or system-level training settings, as it does not conduct experiments. |