In recent years, several frameworks and systems have been proposed that extend Inductive Logic programming (ILP) to the answer set programming (ASP) paradigm. In ILP, examples must all be explained by a hypothesis tog...
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In recent years, several frameworks and systems have been proposed that extend Inductive Logic programming (ILP) to the answer set programming (ASP) paradigm. In ILP, examples must all be explained by a hypothesis together with a given background knowledge. In existing systems, the background knowledge is the same for all examples;however, examples may be context-dependent. This means that some examples should be explained in the context of some information, whereas others should be explained in different contexts. In this paper, we capture this notion and present a context-dependent extension of the Learning from Ordered answersets framework. In this extension, contexts can be used to further structure the background knowledge. We then propose a new iterative algorithm, ILASP2i, which exploits this feature to scale up the existing ILASP2 system to learning tasks with large numbers of examples. We demonstrate the gain in scalability by applying both algorithms to various learning tasks. Our results show that, compared to ILASP2, the newly proposed ILASP2i system can be two orders of magnitude faster and use two orders of magnitude less memory, whilst preserving the same average accuracy.
We show how a bi-directional grammar can be used to specify and verbalise answerset programs in controlled natural language. We start from a program specification in controlled natural language and translate this spe...
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We show how a bi-directional grammar can be used to specify and verbalise answerset programs in controlled natural language. We start from a program specification in controlled natural language and translate this specification automatically into an executable answerset program. The resulting answerset program can be modified following certain naming conventions and the revised version of the program can then be verbalised in the same subset of natural language that was used as specification language. The bi-directional grammar is parametrised for processing and generation, deals with referring expressions, and exploits symmetries in the data structure of the grammar rules whenever these grammar rules need to be duplicated. We demonstrate that verbalisation requires sentence planning in order to aggregate similar structures with the aim to improve the readability of the generated specification. Without modifications, the generated specification is always semantically equivalent to the original one;our bi-directional grammar is the first one that allows for semantic round-tripping in the context of controlled natural language processing.
Studying the performance of logic tools on solving a specific problem can bring new insights on the use of different paradigms. This paper provides an empirical evaluation of logic-based encodings for a well known boa...
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ISBN:
(纸本)9783319653402;9783319653396
Studying the performance of logic tools on solving a specific problem can bring new insights on the use of different paradigms. This paper provides an empirical evaluation of logic-based encodings for a well known board game: Ricochet Robots. Ricochet Robots is a board game where the goal is to find the smallest number of moves needed for one robot to move from the initial position to a target position, while taking into account the existing barriers and other robots. Finding a solution to the Ricochet Robots problem is NP-hard. In this work we develop logic-based encodings for the Ricochet Robots problem to feed into Boolean Satisfiability (SAT) solvers. When appropriate, advanced techniques are applied to further boost the performance of a solver. A comparison between the performance of SAT solvers and an existing ASP solution clearly shows that SAT is by far the more adequate technology to solve the Ricochet Robots problem.
Management of chronic diseases such as chronic heart failure (CHF) is a major problem in health care. A standard approach followed by the medical community is to have a committee of experts develop guidelines that all...
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Management of chronic diseases such as chronic heart failure (CHF) is a major problem in health care. A standard approach followed by the medical community is to have a committee of experts develop guidelines that all physicians should follow. These guidelines typically consist of a series of complex rules that make recommendations based on a patient's information. Due to their complexity, often the guidelines are ignored or not complied with at all. It is not even clear whether it is humanly possible to follow these guidelines due to their length and complexity. For instance, for CHF, the guidelines run nearly eighty pages. In this paper we describe a physician-advisory system for CHF management that codes the entire set of clinical practice guidelines for CHF using answer set programming (ASP). Our approach is based on developing reasoning templates, that we call knowledge patterns, and using them to systemically code the clinical guidelines for CHF as ASP rules. Use of the knowledge patterns greatly facilitates the development of our system. Given a patient's medical information, our system generates a recommendation for treatment just as a human physician would, using the guidelines. Our system works even in the presence of incomplete information.
We describe the design of the OLPS system, an implementation of the preferred answerset semantics for ordered logic programs. The basic algorithm we propose computes the extended answersets of a simple program using...
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ISBN:
(纸本)3540243623
We describe the design of the OLPS system, an implementation of the preferred answerset semantics for ordered logic programs. The basic algorithm we propose computes the extended answersets of a simple program using an intuitive 9-valued lattice, called T-9. During the computation, this lattice is employed to keep track of the status of the literals and the rules while evolving to a solution. It turns out that the basic algorithm needs little modification in order to be able to compute the preferred answersets of an ordered logic program. We illustrate the system using an example from diagnostic reasoning and we present some preliminary benchmark results comparing OLPS with existing answerset solvers such as SMODELS and DLV.
Software development teams meet increasing requirements to implement cybersecurity management in compliance with standards and regulations. However, adopting a compliant cybersecurity management system and DevSecOps p...
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ISBN:
(纸本)9798400709845
Software development teams meet increasing requirements to implement cybersecurity management in compliance with standards and regulations. However, adopting a compliant cybersecurity management system and DevSecOps practices as part of a software development process has turned out to be tedious and expensive in practice. Open-source communities and open ecosystems, which lack tools and realistic practices for compliant cybersecurity management, face these difficulties as well. This paper suggests a set of requirements and a solution that are based on long-term experience in adopting standard compliant DevSecOps processes in industry. The proposed solution, called Cyberismo, facilitates the adoption of compliance and cybersecurity management, improves collaboration on cybersecurity in company internal projects, cross-company projects, and open-source projects, and automates the compliance and cybersecurity management in software development by way of an open information model representation format, and an open-source tool to manage the information model. As the information model uses a simple plain text format that can be managed by automated DevSecOps tool chains, it can be understood as an instance of the Everything as Code and Security as Code paradigms. The proposed solution is designed as modular, tailorable to the organisation and its existing tools, and flexible enough to model both process- and technology-related information. It automates both the validation of how compliance requirements have been met and the gathering and archiving of evidence of compliance. The information model is mapped to a logic program conforming to the answer set programming (ASP) paradigm for knowledge representation. The mapping enables flexible query evaluation and reasoning, including the calculation of performance measures and automated policy checks. However, developers, product owners and other end-users of the solution do not necessarily need to know how to write logic progr
The Routing and Wavelength Assignment (RWA) problem is an optical networking problem aiming to improve data transmission by eliminating optoelectronic conversions through the network. RWA problem is in the set of NP-c...
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ISBN:
(纸本)9781614993209;9781614993193
The Routing and Wavelength Assignment (RWA) problem is an optical networking problem aiming to improve data transmission by eliminating optoelectronic conversions through the network. RWA problem is in the set of NP-complete problems [3] and thus is also an interesting problem form a computational point of view. It can be solved in different flavours, being the Static Lightpath Establishment (SLE) the one we consider here. In this work we present ASP encodings for the problem. Then, we solve them with ASP solvers and we empirically compare them with previous approaches.
Stable models of logic programs have been studied by many researchers, mainly because of their role in the foundations of answer set programming. This is a review of some of the definitions of the concept of a stable ...
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ISBN:
(纸本)9783642150241
Stable models of logic programs have been studied by many researchers, mainly because of their role in the foundations of answer set programming. This is a review of some of the definitions of the concept of a stable model that have been proposed in the literature. These definitions are equivalent to each other, at least when applied to traditional Prolog-style programs, but there are reasons why each of them is valuable and interesting. A new characterization of stable models can suggest an alternative picture of the intuitive meaning of logic programs;or it can lead to new algorithms for generating stable models;or it can work better than others when we turn to generalizations of the traditional syntax that are important from the perspective of answer set programming;or it can be more convenient for use in proofs;or it can be interesting simply because it demonstrates a relationship between seemingly unrelated ideas.
We present a novel approach to gaining a machine understanding of a legal document and then modelling the logic of that document in an integrated process. This paper describes a smart editor that uses a declarative la...
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ISBN:
(纸本)9783031361890;9783031361906
We present a novel approach to gaining a machine understanding of a legal document and then modelling the logic of that document in an integrated process. This paper describes a smart editor that uses a declarative language to represent both the ontology and logic models of a legal document. A document is incrementally elaborated in a fixed sequence of steps beginning with an ontology discovery step that identifies the explicit and implicit artefacts and applicable constraints. This information is used to generate code representations paired with words and icons which provide the foundation required for modelling the legal logic. The pairing with words and icons achieves a formal correspondence that allows logic modelling via either a textual or a graphical means. Similarly, this mechanism also supports both verbal and visual user feedback, enhancing user understanding. The tree of rules produced during this process is embedded in the original legal document, which can then be used as a smart contract on a modified blockchain. The integrated use of a declarative language auto-generated from a smart user interface for modelling both the ontology and the logic of a legal document, provides a simplicity and agility that enables domain experts to create and test custom smart contracts.
In recent years, several frameworks and systems have been proposed that extend Inductive Logic programming (ILP) to the answer set programming (ASP) paradigm. In ILP, examples must all be explained by a hypothesis tog...
详细信息
In recent years, several frameworks and systems have been proposed that extend Inductive Logic programming (ILP) to the answer set programming (ASP) paradigm. In ILP, examples must all be explained by a hypothesis together with a given background knowledge. In existing systems, the background knowledge is the same for all examples;however, examples may be context-dependent. This means that some examples should be explained in the context of some information, whereas others should be explained in different contexts. In this paper, we capture this notion and present a context-dependent extension of the Learning from Ordered answersets framework. In this extension, contexts can be used to further structure the background knowledge. We then propose a new iterative algorithm, ILASP2i, which exploits this feature to scale up the existing ILASP2 system to learning tasks with large numbers of examples. We demonstrate the gain in scalability by applying both algorithms to various learning tasks. Our results show that, compared to ILASP2, the newly proposed ILASP2i system can be two orders of magnitude faster and use two orders of magnitude less memory, whilst preserving the same average accuracy.
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