scholarly journals Modular action language

2015 ◽  
Vol 16 (2) ◽  
pp. 189-235 ◽  
Author(s):  
DANIELA INCLEZAN ◽  
MICHAEL GELFOND
Keyword(s):  
Logic Programming ◽  
Medium Size ◽  
Programming System ◽  
Problem Structuring ◽  
System Description ◽  
Action Languages ◽  
Special Cases ◽  
Action Language ◽  
Stepwise Development ◽  
High Level

AbstractThe paper introduces a new modular action language,${\mathcal ALM}$, and illustrates the methodology of its use. It is based on the approach of Gelfond and Lifschitz (1993,Journal of Logic Programming 17, 2–4, 301–321; 1998,Electronic Transactions on AI 3, 16, 193–210) in which a high-level action language is used as a front end for a logic programming system description. The resulting logic programming representation is used to perform various computational tasks. The methodology based on existing action languages works well for small and even medium size systems, but is not meant to deal with larger systems that requirestructuring of knowledge.$\mathcal{ALM}$is meant to remedy this problem. Structuring of knowledge in${\mathcal ALM}$is supported by the concepts ofmodule(a formal description of a specific piece of knowledge packaged as a unit),module hierarchy, andlibrary, and by the division of a system description of${\mathcal ALM}$into two parts:theoryandstructure. Atheoryconsists of one or more modules with a common theme, possibly organized into a module hierarchy based on adependency relation. It contains declarations of sorts, attributes, and properties of the domain together with axioms describing them.Structuresare used to describe the domain's objects. These features, together with the means for defining classes of a domain as special cases of previously defined ones, facilitate the stepwise development, testing, and readability of a knowledge base, as well as the creation of knowledge representation libraries.

Declarative Planning and Knowledge Representation in an Action Language

2011 ◽  
pp. 192-221 ◽  
Author(s):  
Thomas Eiter ◽  
Wolfgang Faber ◽  
Gerald Pfeifer
Keyword(s):  
Knowledge Representation ◽  
Logic Programming ◽  
Planning System ◽  
Epistemic State ◽  
Action Languages ◽  
Knowledge States ◽  
Action Language ◽  
High Level ◽  
Planning Problems ◽  
Complex Planning

This chapter introduces planning and knowledge representation in the declarative action language K. Rooted in the area of Knowledge Representation & Reasoning, action languages like K allow the formalization of complex planning problems involving non-determinism and incomplete knowledge in a very flexible manner. By giving an overview of existing planning languages and comparing these against our language, we aim on further promoting the applicability and usefulness of high-level action languages in the area of planning. As opposed to previously existing languages for modeling actions and change, K adopts a logic programming view where fluents representing the epistemic state of an agent might be true, false or undefined in each state. We will show that this view of knowledge states can be fruitfully applied to several well-known planning domains from the literature as well as novel planning domains. Remarkably, K often allows to model problems more concisely than previous action languages. All the examples given can be tested in an available implementation, the DLVK planning system.

Declarative Planning and Knowledge Representation in an Action Language

2005 ◽  
pp. 1-34 ◽  
Author(s):  
Thomas Eiter ◽  
Wolfgang Faber ◽  
Gerald Pfeifer ◽  
Axel Polleres
Keyword(s):  
Knowledge Representation ◽  
Logic Programming ◽  
Planning System ◽  
Epistemic State ◽  
Action Languages ◽  
Knowledge States ◽  
Action Language ◽  
High Level ◽  
Planning Problems ◽  
Complex Planning

This chapter introduces planning and knowledge representation in the declarative action language K. Rooted in the area of Knowledge Representation & Reasoning, action languages like K allow the formalization of complex planning problems involving non-determinism and incomplete knowledge in a very flexible manner. By giving an overview of existing planning languages and comparing these against our language, we aim on further promoting the applicability and usefulness of high-level action languages in the area of planning. As opposed to previously existing languages for modeling actions and change, K adopts a logic programming view where fluents representing the epistemic state of an agent might be true, false or undefined in each state. We will show that this view of knowledge states can be fruitfully applied to several well-known planning domains from the literature as well as novel planning domains. Remarkably, K often allows to model problems more concisely than previous action languages. All the examples given can be tested in an available implementation, the DLVK planning system.

ECLiPSe – From LP to CLP

2011 ◽  
Vol 12 (1-2) ◽  
pp. 127-156 ◽  
Author(s):  
JOACHIM SCHIMPF ◽  
KISH SHEN
Keyword(s):  
Logic Programming ◽  
Constraint Programming ◽  
Combinatorial Problem ◽  
Third Party ◽  
Programming System ◽  
Development Environment ◽  
Control Language ◽  
Extended Prolog ◽  
High Level ◽  
And Control

AbstractECLiPSe is a Prolog-based programming system, aimed at the development and deployment of constraint programming applications. It is also used for teaching most aspects of combinatorial problem solving, for example, problem modelling, constraint programming, mathematical programming and search techniques. It uses an extended Prolog as its high-level modelling and control language, complemented by several constraint solver libraries, interfaces to third-party solvers, an integrated development environment and interfaces for embedding into host environments. This paper discusses language extensions, implementation aspects, components, and tools that we consider relevant on the way from Logic Programming to Constraint Logic Programming.

Action language ℬ𝒞+

2015 ◽  
Vol 30 (4) ◽  
pp. 899-922 ◽  
Author(s):  
Joseph Babb ◽  
Joohyung Lee
Keyword(s):  
Main Idea ◽  
Answer Set Programming ◽  
Stable Model ◽  
Formal Models ◽  
Transition Systems ◽  
Action Languages ◽  
Action Language ◽  
Language Constructs ◽  
High Level ◽  
Answer Set

Abstract Action languages are formal models of parts of natural language that are designed to describe effects of actions. Many of these languages can be viewed as high-level notations of answer set programs structured to represent transition systems. However, the form of answer set programs considered in the earlier work is quite limited in comparison with the modern Answer Set Programming (ASP) language, which allows several useful constructs for knowledge representation, such as choice rules, aggregates and abstract constraint atoms. We propose a new action language called BC +, which closes the gap between action languages and the modern ASP language. The main idea is to define the semantics of BC + in terms of general stable model semantics for propositional formulas, under which many modern ASP language constructs can be identified with shorthands for propositional formulas. Language BC  + turns out to be sufficiently expressive to encompass the best features of other action languages, such as languages B , C , C + and BC . Computational methods available in ASP solvers are readily applicable to compute BC +, which led to an implementation of the language by extending system cplus2asp .

Compiler-Aided Run-Time Performance Speed-Up in Super-Scalar Processor

10.28945/3391 ◽  
2009 ◽  
Author(s):  
Moshe Pelleh
Keyword(s):  
Embedded Systems ◽  
Embedded System ◽  
General Purpose ◽  
Experimental Results ◽  
Medium Size ◽  
Organic System ◽  
Software Application ◽  
Organic Systems ◽  
Special Cases ◽  
Run Time

In our world, where most systems become embedded systems, the approach of designing embedded systems is still frequently similar to the approach of designing organic systems (or not embedded systems). An organic system, like a personal computer or a work station, must be able to run any task submitted to it at any time (with certain constrains depending on the machine). Consequently, it must have a sophisticated general purpose Operating System (OS) to schedule, dispatch, maintain and monitor the tasks and assist them in special cases (particularly communication and synchronization between them and with external devices). These OSs require an overhead on the memory, on the cache and on the run time. Moreover, generally they are task oriented rather than machine oriented; therefore the processor's throughput is penalized. On the other hand, an embedded system, like an Anti-lock Braking System (ABS), executes always the same software application. Frequently it is a small or medium size system, or made up of several such systems. Many small or medium size embedded systems, with limited number of tasks, can be scheduled by our proposed hardware architecture, based on the Motorola 500MHz MPC7410 processor, enhancing its throughput and avoiding the software OS overhead, complexity, maintenance and price. Encouraged by our experimental results, we shall develop a compiler to assist our method. In the meantime we will present here our proposal and the experimental results.

scholarly journals Solving Probability Problems in Natural Language

2017 ◽  
Author(s):  
Anton Dries ◽  
Angelika Kimmig ◽  
Jesse Davis ◽  
Vaishak Belle ◽  
Luc de Raedt
Keyword(s):  
Natural Language ◽  
Discrete Mathematics ◽  
Second Step ◽  
Programming System ◽  
Mathematics Textbooks ◽  
Intellectual Skill ◽  
Correct Model ◽  
Level Model ◽  
End To End ◽  
High Level

The ability to solve probability word problems such as those found in introductory discrete mathematics textbooks, is an important cognitive and intellectual skill. In this paper, we develop a two-step end-to-end fully automated approach for solving such questions that is able to automatically provide answers to exercises about probability formulated in natural language.In the first step, a question formulated in natural language is analysed and transformed into a high-level model specified in a declarative language. In the second step, a solution to the high-level model is computed using a probabilistic programming system. On a dataset of 2160 probability problems, our solver is able to correctly answer 97.5% of the questions given a correct model. On the end-to-end evaluation, we are able to answer 12.5% of the questions (or 31.1% if we exclude examples not supported by design).

scholarly journals Constraint Problem Specification as Compression

10.29007/7ths ◽  
2018 ◽  
Author(s):  
Steve Prestwich ◽  
S. Armagan Tarim ◽  
Roberto Rossi
Keyword(s):  
Logic Programming ◽  
Data Compression ◽  
Constraint Programming ◽  
Auxiliary Problem ◽  
Combinatorial Problems ◽  
Specification Languages ◽  
Constraint Problem ◽  
High Level ◽  
Natural Way ◽  
Comparable Size

Constraint Programming is a powerful and expressive framework for modelling and solving combinatorial problems. It is nevertheless not always easy to use, which has led to the development of high-level specification languages. We show that Constraint Logic Programming can be used as a meta-language to describe itself more compactly at a higher level of abstraction. This can produce problem descriptions of comparable size to those in existing specification languages, via techniques similar to those used in data compression. An advantage over existing specification languages is that, for a problem whose specification requires the solution of an auxiliary problem, a single specification can unify the two problems. Moreover, using a symbolic representation of domain values leads to a natural way of modelling channelling constraints.

scholarly journals A refinement-based development of a distributed signalling system

2021 ◽  
Author(s):  
Paulius Stankaitis ◽  
Alexei Iliasov ◽  
Tsutomu Kobayashi ◽  
Yamine Aït-Ameur ◽  
Fuyuki Ishikawa ◽  
...  
Keyword(s):  
Model Verification ◽  
Modelling Language ◽  
Distributed Protocol ◽  
Rigorous Approach ◽  
Railway Systems ◽  
Main Challenge ◽  
Stepwise Development ◽  
Railway Signalling ◽  
High Level ◽  
Signalling Systems

AbstractThe decentralised railway signalling systems have a potential to increase capacity, availability and reduce maintenance costs of railway networks. However, given the safety-critical nature of railway signalling and the complexity of novel distributed signalling solutions, their safety should be guaranteed by using thorough system validation methods. To achieve such a high-level of safety assurance of these complex signalling systems, scenario-based testing methods are far from being sufficient despite that they are still widely used in the industry. Formal verification is an alternative approach which provides a rigorous approach to verifying complex systems and has been successfully used in the railway domain. Despite the successes, little work has been done in applying formal methods for distributed railway systems. In our research we are working towards a multifaceted formal development methodology of complex railway signalling systems. The methodology is based on the Event-B modelling language which provides an expressive modelling language, a stepwise development and a proof-based model verification. In this paper, we present the application of the methodology for the development and verification of a distributed protocol for reservation of railway sections. The main challenge of this work is developing a distributed protocol which ensures safety and liveness of the distributed railway system when message delays are allowed in the model.

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