An Online Logic Programming Development Environment

Authors: Christian Reotutar, Mbathio Diagne, Evgenii Balai, Edward Wertz, Peter Lee, Shao-Lon Yeh, Yuanlin Zhang

AAAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental We developed an online answer set programming environment with simple interface and self contained file system. It is expected to make the teaching of answer set programming more effective and help us to reach more students. ... Our online environment, with a carefully designed simple interface and a self contained file system, provided easy access and sharing, reduced the learning curve, and removed the installation and maintenance expenses, by our experience of using it in our teaching in Fall 2015.
Researcher Affiliation Academia 1Department of Computer Science, Johns Hopkins University, USA 2Department of Mathematics, Minneapolis Community and Technical College, USA 3Department of Computer Science, Texas Tech University, USA 4Department of EECS, University of California, Berkeley, USA 5Lubbock High School, Lubbock, Texas, USA
Pseudocode No The paper does not contain any pseudocode or clearly labeled algorithm blocks.
Open Source Code No The paper mentions the system is 'avail at http://goo.gl/uk SZET' which appears to be a link to the live application, not its source code. There is no explicit statement of source code release.
Open Datasets No The paper describes the development of an online environment and its use in teaching, not experiments involving datasets with training splits.
Dataset Splits No The paper does not mention any validation splits or a validation dataset.
Hardware Specification No No specific hardware used for running experiments or developing the system is mentioned.
Software Dependencies No The paper mentions 'front end (FE) in Java Script, processing unit (PU) in PHP, and back end (BE) (SPARC solver (Balai, Gelfond, and Zhang 2013) and My SQL database system)' but does not provide specific version numbers for these software components.
Experiment Setup No The paper describes the system's design and its observed benefits in a teaching context, but it does not detail an experimental setup with hyperparameters or specific training configurations typical of machine learning or simulation experiments.