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 Shift Toward Open and Reproducible AI Research," Under Review, 2026. doi: 10.48550/arXiv.2606.16974..
Revising Beliefs and Intentions in Stochastic Environments
Authors: Nima Motamed, Natasha Alechina, Mehdi Dastani, Dragan Doder
IJCAI 2024 | Venue PDF | LLM Run Details | Input Tokens: 22,155 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 3,593 Total number of tokens produced by the LLM (including reasoning/thinking tokens) for this paper's analysis.
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we initiate the study of belief and intention revision in stochastic environments, where an agent s beliefs and intentions are specified in a decidable probabilistic temporal logic. We then provide general Katsuno & Mendelzon-style representation theorems for both belief and intention revision, giving clear semantic characterizations of revision methods. |
| Researcher Affiliation | Academia | 1Utrecht University, The Netherlands 2Open University, The Netherlands EMAIL |
| Pseudocode | No | The paper presents theoretical definitions, logic syntax, semantics, and proofs, but does not include any pseudocode or algorithm blocks. |
| Open Source Code | No | The paper is a theoretical work and does not mention releasing any source code for its described methodologies. |
| Open Datasets | No | The paper is theoretical and does not involve experimental evaluation with datasets. |
| Dataset Splits | No | The paper is theoretical and does not involve experimental evaluation with dataset splits. |
| Hardware Specification | No | The paper is theoretical and does not describe any experimental hardware specifications. |
| Software Dependencies | No | The paper is theoretical and does not specify any software dependencies with version numbers required for experimental replication. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup details or hyperparameters. |