Answer Set programming (ASP) is an established logic-based programming paradigm which has been successfully applied for solving complex problems since it features efficient implementations. In previous work we showed ...
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We present a solution to real-world train scheduling problems, involving routing, scheduling, and optimization, based on Answer Set programming (ASP). To this end, we pursue a hybrid approach that extends ASP with dif...
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Forgetting as a knowledge management operation has received much less attention than operations like inference or revision. It was mainly in the area of logic programming that techniques and axiomatic properties have ...
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We present an operational semantics for time-aware business processes, that is, processes modeling the execution of business activities, whose durations are subject to linear constraints over the integers. We assume t...
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We present an operational semantics for time-aware business processes, that is, processes modeling the execution of business activities, whose durations are subject to linear constraints over the integers. We assume that some of the durations are controllable, that is, they can be determined by the organization that executes the process, while others are uncontrollable, that is, they are determined by the external world. Then, we consider controllability properties, which guarantee the completion of the execution of the process, satisfying the given duration constraints, independently of the values of the uncontrollable durations. Controllability properties are encoded by quantified reachability formulas, where the reachability predicate is recursively defined by means of constrained Horn clauses (CHCs). These clauses are automatically derived from the operational semantics of the process. Finally, we present two algorithms for solving the so called weak and strong controllability problems. Our algorithms reduce these problems to the verification of a set of quantified integer constraints, which are simpler than the original quantified reachability formulas, and can effectively be handled by state-of-the-art CHC solvers.
Bridge is a trick-taking card game requiring the ability to evaluate probabilities since it is a game of incomplete information where each player only sees its cards. In order to choose a strategy, a player needs to g...
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The s-semantics makes it possible to explicitly deal with variables in program answers. So it seems suitable for programs using nonground data structures, like open lists. However it is difficult to find published exa...
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Data Structures and algorithms are core topics taught in all Computer Science degrees. Yet for all the commonality in teaching these topics there is no universally accepted method for presenting the material. Some fac...
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ISBN:
(数字)9781728142913
ISBN:
(纸本)9781728142920
Data Structures and algorithms are core topics taught in all Computer Science degrees. Yet for all the commonality in teaching these topics there is no universally accepted method for presenting the material. Some faculty and students will prefer a more graphical presentation with accompany lecture, others will prefer a more textual approach with pseudo-code, others will use a combination of both. While any of these approaches can be effective they all suffer from the same two problems 1) neither has formally defined what the students specifically needs to do to implement a data structure or algorithm, 2) neither can be used by the student to verify that what they have implemented is correct. By writing Prolog for common data structures and algorithms, we can avoid these problems because Prolog provides us with a formal language for specifying a definition and once written the definition can be executed in the form of a proof to show how the data structure or algorithm should perform under various conditions.
Generalising and re-using knowledge learned while solving one problem instance has been neglected by state-of-the-art answer set solvers. We suggest a new approach that generalises learned nogoods for reuse to speed-u...
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Reaction Systems (RSs) are a successful computational framework inspired by biological systems. A RS pairs a set of entities with a set of reactions over them. Entities can be used to enable or inhibit each reaction, ...
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