Logic based modeling and analysis of workflows
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Expert Systems: Introduction to First and Second Generation and Hybrid Knowledge Based Systems
Expert Systems: Introduction to First and Second Generation and Hybrid Knowledge Based Systems
Knowledge Representation, Reasoning, and Declarative Problem Solving
Knowledge Representation, Reasoning, and Declarative Problem Solving
Elements Of Finite Model Theory (Texts in Theoretical Computer Science. An Eatcs Series)
Elements Of Finite Model Theory (Texts in Theoretical Computer Science. An Eatcs Series)
The DLV system for knowledge representation and reasoning
ACM Transactions on Computational Logic (TOCL)
Answer set based design of knowledge systems
Annals of Mathematics and Artificial Intelligence
YAWL: yet another workflow language
Information Systems
Well-founded semantics and the algebraic theory of non-monotone inductive definitions
LPNMR'07 Proceedings of the 9th international conference on Logic programming and nonmonotonic reasoning
Using Lightweight Inference to Solve Lightweight Problems
LPNMR '09 Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning
Plato: a compiler for interactive web forms
PADL'11 Proceedings of the 13th international conference on Practical aspects of declarative languages
Constraint Propagation for First-Order Logic and Inductive Definitions
ACM Transactions on Computational Logic (TOCL)
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There are many reasons why software can be hard to implement. For important classes of applications, the main source of complexity is the domain knowledge that is involved. One such class is that of configuration software, which serves to assist a user in making choices in accordance with certain constraints. For instance, consider an application that helps students compose a study program that complies with all relevant university regulations. The reason why this may be difficult to implement is that these regulations can get quite complicated, making them hard to handle, at least for imperative programming methods. A better approach might be to follow the paradigm of a knowledge base system: explicitly represent the domain knowledge in a declarative way, and implement the behavior of the application by performing various logical inference methods on it. Doing this well, however, requires that a number of different components be got right. Most importantly, we need an expressive and purely declarative knowledge representation language, together with a set of useful inference methods. In this paper, we present a framework for implementing this kind of software, based on a rich extension of first-order logic.