Ranked Programming
Authors: Tjitze Rienstra
IJCAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper we combine probabilistic programming methodology with ranking theory and develop a ranked programming language. We use the Scheme programming language a basis and extend it with the ability to express both normal and exceptional behaviour of a model, and perform inference on such models. Like probabilistic programming, our approach provides a simple and flexible way to represent and reason with models involving uncertainty, but using a coarser grained and computationally simpler kind of uncertainty. |
| Researcher Affiliation | Academia | Tjitze Rienstra Institute for Web Science and Technologies, University of Koblenz-Landau, Germany rienstra@uni-koblenz.de |
| Pseudocode | No | The paper provides Scheme code examples to illustrate the language's functionality, but these are actual code snippets rather than abstract pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | Yes | An implementation was developed using the Racket Scheme dialect as a basis. For download and instructions see https://pkgd.racket-lang.org/pkgn/ package/ranked-programming. |
| Open Datasets | No | The paper primarily introduces a programming language and demonstrates its capabilities through illustrative examples (e.g., a ranking network, boolean circuit diagnosis, hidden Markov model, ranked automata). It does not use or refer to publicly available datasets for training, validation, or testing in a typical machine learning context. |
| Dataset Splits | No | The paper describes a new programming language and illustrates its use with examples, rather than conducting empirical studies that would involve training, validation, or test dataset splits. |
| Hardware Specification | No | The paper introduces a programming language and its theoretical semantics, followed by illustrative examples. It does not mention any specific hardware (e.g., GPU/CPU models, cloud instances) used for the development or execution of the language or its examples. |
| Software Dependencies | No | The paper mentions that the language is "based on the Scheme programming language" and that an "implementation was developed using the Racket Scheme dialect as a basis." However, it does not specify version numbers for Racket or any other software libraries, which would be necessary for full reproducibility. |
| Experiment Setup | No | The paper introduces a programming language and demonstrates its use with various examples. These demonstrations are conceptual and illustrative, not formal experiments that would involve specifying hyperparameters, model initialization, or system-level training settings. |