Workshop on Applications of Logic Programming (AppLP)
Molham Aref LogicBlox, Inc.
Business intelligence, enterprise decision making, ...
Marcello Balduccini Drexel University
Flight control systems, industrial scheduling, cybersecurity, information retrieval, ...
C.R. Ramakrishnan Stony Brook University
Model checking, program analysis, probabilistic inference, planning, ...
Francesco Ricca University of Calabria
Call classification, team building, touristic package allotment, data cleaning, ...
Title: Solver-Aided Declarative Programming
Speaker: Molham Aref
I will summarize our work on a declarative programming language that offers native language support for expressing predictive (e.g. machine learning) and prescriptive (e.g. combinatorial optimization) analytics. The presentation gives an overview of the platform and the language. In particular, it focuses on the important role of integrity constraints, which are used not only for maintaining data integrity, but also, for example, for the specification of complex optimization problems and probabilistic programming.
Title: What Tweety-the-Penguin and Faulty Suitcases Tell Us about Productivity, Cybersecurity and Data Sciences
Speaker: Marcello Balduccini
The areas of research of commonsense, reasoning about actions and change, and constraint satisfaction have a long-standing tradition in the knowledge representation community. These areas have frequently developed independently of each other, but various forms of their combination have proven extremely useful for practical applications.
In this talk, we aim to convey some sense of the breadth of applications yielded by the research at the intersection of commonsense, reasoning about actions and change, and constraint satisfaction. We will start from our early, and somewhat unexpected, success in solving industrial-sized problems with a planning and diagnostic system for the Space Shuttle, and we will then expand to later work on hybrid reasoning, industrial scheduling, cybersecurity, and information retrieval.
Title: Declarative Probabilistic Programming for Program Analysis
Speaker: C.R. Ramakrishnan
Logic Programming has been successfully used for deriving efficient program analyzers and model checkers from succinct, high-level specifications. In this talk, we will examine what made logic programming especially suited for this task. We will survey some of the key technical developments that helped in these applications. We will also consider extensions to traditional logic programming semantics and inference techniques to treat probabilistic systems, and describe current work in the analysis of programs and models that use these extensions.
Title: Applying ASP in Industrial Contexts: Lessons Learned and Current Directions
Speaker: Francesco Ricca
Answer Set Programming (ASP) is a declarative programming paradigm that has been proposed in the area of logic programming and non monotonic reasoning. ASP has become a popular choice for solving complex problems, as witnessed by the numerous scientific applications that are based on ASP, and it is nowadays attracting increasing interest also beyond the scientific community.
We report on the development of some applications of ASP in industrial contexts. We focus on the lessons we have learned and on current developments. We outline the advantages of ASP from the software engineering point of view, and we stress the importance of extending tools and development environments to speed-up and simplify the implementation of real-world applications.