Modular Systems with Preferences
Authors: Alireza Ensan, Eugenia Ternovska
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We propose a versatile framework for combining knowledge bases in modular systems with preferences. In our formalism, each module (knowledge base) can be specified in a different language. We define the notion of a preference-based modular system that includes a formalization of metapreferences. We prove that our formalism is robust in the sense that the operations for combining modules preserve the notion of a preference-based modular system. Finally, we formally demonstrate correspondences between our framework and the related preference formalisms of cp-nets and preference-based planning. |
| Researcher Affiliation | Academia | Alireza Ensan and Eugenia Ternovska Simon Fraser University Canada {aensan,ter}@sfu.ca |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any concrete access to source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not use or refer to any publicly available datasets for training or evaluation. |
| Dataset Splits | No | The paper is theoretical and does not involve dataset splits for training, validation, or testing. |
| Hardware Specification | No | The paper is theoretical and does not specify any hardware details used for running experiments. |
| Software Dependencies | No | The paper is theoretical and does not specify any software dependencies with version numbers for reproducing experiments. |
| Experiment Setup | No | The paper is theoretical and does not provide specific experimental setup details, such as hyperparameters or training configurations. |