The KB paradigm and its application to interactive configuration

Hertum, Pieter Van; Dasseville, Ingmar; Janssens, Gerda; Denecker, Marc

doi:10.1017/s1471068416000156

Cited by 10 publications

(9 citation statements)

References 31 publications

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“…From a systems point of view, a direction for future work is to make our approach interactive, essentially allowing ZEBRATUTOR to be called while a user is solving the puzzle and to implement in more serious domains such as for instance interactive configuration in which a human and a search engine cooperate to solve some configuration problem and the human can often be interested in understanding why the system did certain derivations [44,45].…”

Section: Discussion Future Work and Conclusionmentioning

confidence: 99%

A framework for step-wise explaining how to solve constraint satisfaction problems

Bogaerts,

Gamba,

Guns

2020

Preprint

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We explore the problem of step-wise explaining how to solve constraint satisfaction problems, with a use case on logic grid puzzles. More specifically, we study the problem of explaining the inference steps that one can take during propagation, in a way that is easy to interpret for a person. Thereby, we aim to give the constraint solver explainable agency, which can help in building trust in the solver by being able to understand and even learn from the explanations. The main challenge is that of finding a sequence of simple explanations, where each explanation should aim to be as cognitively easy as possible for a human to verify and understand. This contrasts with the arbitrary combination of facts and constraints that the solver may use when propagating. We propose the use of a cost function to quantify how simple an individual explanation of an inference step is, and identify the explanation-production problem of finding the best sequence of explanations of a CSP. Our approach is agnostic of the underlying constraint propagation mechanisms, and can provide explanations even for inference steps resulting from combinations of constraints. In case multiple constraints are involved, we also develop a mechanism that allows to break the most difficult steps up and thus gives the user the ability to zoom in on specific parts of the explanation. Our proposed algorithm iteratively constructs the explanation sequence by using an optimistic estimate of the cost function to guide the search for the best explanation at each step. Our experiments on logic grid puzzles show the feasibility of the approach in terms of the quality of the individual explanations and the resulting explanation sequences obtained.

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Section: Discussion Future Work and Conclusionmentioning

confidence: 99%

A framework for step-wise explaining how to solve constraint satisfaction problems

Bogaerts,

Gamba,

Guns

2020

Preprint

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“…This is a preliminary work with the final objective of developing an interactive product configuration system [1] [10]. Identification and encoding of more concepts such as resource constraints, default values, user preferences among others would be the next step.…”

Section: Future Workmentioning

confidence: 99%

Product Configuration in Answer Set Programming

Mishra

2021

Electron. Proc. Theor. Comput. Sci.

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This is a preliminary work on configuration knowledge representation which serves as a foundation for building interactive configuration systems in Answer Set Programming (ASP). The major concepts of the product configuration problem are identified and discussed with a bike configuration example. A fact format is developed for expressing product knowledge that is domainspecific and can be mapped from other systems. Finally, a domain-independent ASP encoding is provided that represents the concepts in the configuration problem.

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“…Knowledge-based systems are systems that adhere to the knowledge-based paradigm (KBP). The governing principle of the KBP is the distinction between domain knowledge an sich, and the way this knowledge is used in different use cases [17]. The domain knowledge is formalised and centralised in the knowledge base (KB).…”

Section: Idp and The Knowledge-based Paradigmmentioning

confidence: 99%

Aligning, Interoperating, and Co-executing Air Traffic Control Rules Across PSOA RuleML and IDP

Deryck

Mitsikas

Almpani

et al. 2019

Rules and Reasoning

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This paper studies Knowledge Bases (KBs) in PSOA RuleML and IDP, aligning, interoperating, and co-executing them for a use case of Air Traffic Control (ATC) regulations. We focus on the common core of facts and rules in both languages, explaining basic language features. The used knowledge sources are regulations that are specified in (legal) English, and an aircraft data schema. In the modeling process, inconsistencies in both sources were discovered. We present the discovery process utilizing both specification languages, and highlight their unique features. We introduce three extensions to this ATC KB core: 1) While the current PSOA RuleML does not distinguish the ontology separately from the instance level, IDP does. Hence we specify a vocabulary-enriched version of ATC KB in IDP for knowledge validation. 2) While the current IDP uses relational modeling, PSOA also supports graph modeling. Hence we specify a relationally interoperable graph version of ATC KB in PSOA.3) The KB is extended to include optimization criteria. With this, the determination of an optimal sequence of more than two aircraft is possible.

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The KB paradigm and its application to interactive configuration

Cited by 10 publications

References 31 publications

A framework for step-wise explaining how to solve constraint satisfaction problems

A framework for step-wise explaining how to solve constraint satisfaction problems

Product Configuration in Answer Set Programming

Aligning, Interoperating, and Co-executing Air Traffic Control Rules Across PSOA RuleML and IDP

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