Heuristic Induction of Rate-Based Process Models
Authors: Pat Langley, Adam Arvay
AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We report analyses and experiments that suggest it scales well to complex domains and data sets. ... We also describe an implemented system that incorporates these ideas, and we report experimental studies that demonstrate its ability to identify relevant processes, handle noisy observations, and construct accurate models that relate many variables. |
| Researcher Affiliation | Academia | Pat Langley and Adam Arvay Department of Computer Science, University of Auckland, Private Bag 92019, Auckland 1142, New Zealand |
| Pseudocode | No | The paper describes the RPM system's operation in detail within the text (Section 3.2 'A Regression-Guided Process Modeler'), but it does not include any formal pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide a link to open-source code for the described methodology, nor does it state that the code is available in supplementary materials or upon request. It only mentions 'RPM, an implemented system'. |
| Open Datasets | Yes | Our initial runs focused on published data about a simple predator-prey ecosystem (Veilleux 1979). |
| Dataset Splits | No | The paper mentions 'training data' in the context of mean squared error (Section 4.4), but it does not specify any training, validation, or test splits by percentage, count, or reference to predefined splits. It only refers to 'natural data' and 'synthetic data'. |
| Hardware Specification | No | The paper does not specify any hardware details (e.g., CPU, GPU models, memory) used to run the experiments. It only states that 'RPM finds these models more than 83,000 times faster' which implies computation, but no hardware specifics. |
| Software Dependencies | No | The paper mentions that both RPM and SC-IPM are 'written in Lisp' (Section 4.4), but it does not provide specific version numbers for Lisp or any other software libraries, compilers, or operating systems used in the experiments. |
| Experiment Setup | Yes | If the r2 for any of these equations exceeds a user-specified threshold, then RPM adds the best candidate to its model... Otherwise, it examines triples of processes, and so on, continuing until reaching a user-specified maximum. ... We held the first parameter constant at 600, which seemed sufficient to ensure SC-IPM examines the target structure, and varied the second from 10 to 150 restarts. |