In answer set programming, two groups of rules are considered strongly equivalent if replacing one group by the other within any program does not affect the set of stable models. Jan Heuer has designed and implemented...
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ISBN:
(纸本)9783031436185;9783031436192
In answer set programming, two groups of rules are considered strongly equivalent if replacing one group by the other within any program does not affect the set of stable models. Jan Heuer has designed and implemented a system that verifies strong equivalence of programs in the ASP language mini-gringo. The design is based on the syntactic transformation tau * that converts mini-gringo programs into first-order formulas. Heuer's assertion about tau * that was supposed to justify this procedure turned out to be incorrect, and in this paper we propose an alternative justification for his algorithm. We show also that if tau * is replaced by the simpler and more natural translation nu then the algorithm will still produce correct results.
This system demonstration presents Nemo, a new logic programming engine with a focus on reliability and performance. Nemo is built for data-centric analytic computations, modelled in a fully declarative Datalog dialec...
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This system demonstration presents Nemo, a new logic programming engine with a focus on reliability and performance. Nemo is built for data-centric analytic computations, modelled in a fully declarative Datalog dialect. Its scalability for these tasks matches or exceeds that of leading Datalog systems. We demonstrate uses in reasoning with knowledge graphs and ontologies with 10(5)-10(8) input facts, all on a laptop. Nemo is written in Rust and available as a free and open source tool.
When modelling expert knowledge as logic programs, default negation is very useful, but might lead to there being no stable models. Detecting the exact causes of the incoherence in the logic program manually can becom...
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When modelling expert knowledge as logic programs, default negation is very useful, but might lead to there being no stable models. Detecting the exact causes of the incoherence in the logic program manually can become quite cumbersome, especially in larger programs. Moreover, establishing coherence requires expertise regarding the modelled knowledge as well as technical knowledge about the program and its rules. In this demo, we present the implementation of a workflow that enables knowledge experts to obtain a coherent logic program by modifying it in interaction with a system that explains the causes of the incoherence and provides possible solutions to choose from.
Answer-Set programming (ASP) is a popular declarative reasoning and problem solving formalism. Due to the increasing interest in explainability, several explanation approaches have been developed for ASP. However, whi...
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ISBN:
(纸本)9783031436185;9783031436192
Answer-Set programming (ASP) is a popular declarative reasoning and problem solving formalism. Due to the increasing interest in explainability, several explanation approaches have been developed for ASP. However, while those formalisms are correct and interesting on their own, most are more technical and less oriented towards philosophical or social concepts of explanation. In this work, we study the notion of contrastive explanation, i.e., answering questions of the form "Why P instead of Q?", in the context of ASP. In particular, we are interested in answering why atoms are included in an answer set, whereas others are not. Contrastive explainability has recently become popular due to its strong support from the philosophical, cognitive, and social sciences and its apparent ability to provide explanations that are concise and intuitive for humans. We formally define contrastive explanations for ASP based on counterfactual reasoning about programs. Furthermore, we demonstrate the usefulness of the concept on example applications and give some complexity results. The latter also provide a guideline as to how the explanations can be computed in practice.
Recently, ABA Learning has been proposed as a form of symbolic machine learning for drawing Assumption-Based Argumentation frameworks from background knowledge and positive and negative examples. We propose a novel me...
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Recently, ABA Learning has been proposed as a form of symbolic machine learning for drawing Assumption-Based Argumentation frameworks from background knowledge and positive and negative examples. We propose a novel method for implementing ABA Learning using Answer Set programming as a way to help guide Rote Learning and generalisation in ABA Learning.
Communicating Datalog Programs (CDPs) are a distributed computing model grounded on logic programming: networks of nodes perform Datalog-like computations, leveraging on information coming from incoming messages and d...
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ISBN:
(纸本)9783031450716;9783031450723
Communicating Datalog Programs (CDPs) are a distributed computing model grounded on logic programming: networks of nodes perform Datalog-like computations, leveraging on information coming from incoming messages and databases received from external services. In previous works, the decidability and complexity border of verification for different variants of CDPs was charted. In general, the problem is undecidable, but model-checking of CTL formulas specialized to the data-centric and distributed setting is decidable for CDPs where all data-sources, except the external inputs, are bounded. An intuitive explanation is that "a bounded state is unable to fully take advantage of an unbounded input", a formal justification is missing. However, we note that traditional CDPs have a limited capability of handling external inputs, i.e., they cannot directly compare two successive inputs or messages. Thus, an alternative explanation is that an unbounded data-source does per se not cause undecidability, as long as the CDP cannot compare two successive instances.
This article proposes an approach to the data-aware multi-service application placement problem in Cloud-Edge settings. We propose both declarative programming and a Mixed-Integer Linear programming (MILP) approach to...
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ISBN:
(纸本)9798350304817
This article proposes an approach to the data-aware multi-service application placement problem in Cloud-Edge settings. We propose both declarative programming and a Mixed-Integer Linear programming (MILP) approach to determine eligible placements that minimise operational costs and reduce the number of used nodes to contain the amount of data transfers. After assessing the performance of both approaches, we reconcile them into a methodology that combines the best of the two worlds by exploiting a declarative pre-processing step to boost the MILP solver while determining optimal solutions. We open-sourced the methodology into a prototype that is 10x faster than pure MILP, determines optimal results, and easily accommodates non-numerical constraints on application placements.
Extensions of Answer Set programming with language constructs from temporal logics, such as temporal equilibrium logic over finite traces (TELf), provide an expressive computational framework for modeling dynamic appl...
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ISBN:
(纸本)9783031436185;9783031436192
Extensions of Answer Set programming with language constructs from temporal logics, such as temporal equilibrium logic over finite traces (TELf), provide an expressive computational framework for modeling dynamic applications. In this paper, we study the so-called past-present syntactic subclass, which consists of a set of logic programming rules whose body references to the past and head to the present. Such restriction ensures that the past remains independent of the future, which is the case in most dynamic domains. We extend the definitions of completion and loop formulas to the case of past-present formulas, which allows for capturing the temporal stable models of past-present temporal programs by means of an LTLf expression.
Answer set programs in practice are often subject to change. This can lead to inconsistencies in the modified program due to conflicts between rules which are the results of the derivation of strongly complementary li...
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Answer set programs in practice are often subject to change. This can lead to inconsistencies in the modified program due to conflicts between rules which are the results of the derivation of strongly complementary literals. To facilitate the maintenance of consistency in answer set programs, in this paper we continue work on a recently presented framework that implements interactive conflict resolution by extending the bodies of conflicting rules by suitable literals, so-called 2,-extensions. More precisely, we present strategies to choose 2, -extensions that allow for resolving several conflicts at a time in an order that aims at minimizing (cognitive) efforts. In particular, we present a graphical representation of connections between conflicts and their possible solutions. Such a representation can be utilized to efficiently guide the user through the conflict resolution process by displaying conflicts and suggesting solutions in a suitable order.
Intent-based networking aims at achieving automated network management by allowing users to express desired outcomes rather than manually configure network resources. In this poster paper, by means of an example, we i...
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ISBN:
(纸本)9798400702341
Intent-based networking aims at achieving automated network management by allowing users to express desired outcomes rather than manually configure network resources. In this poster paper, by means of an example, we illustrate our proposal for a declarative and vendor-agnostic methodology to perform intent processing and translation, including static conflict detection and resolution between intents, by leveraging logic programming to determine feasible placements of Virtual Network Function chains. We conclude by pointing out lines for future work.
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