A User's Guide to Gringo, Clasp, Clingo, and Iclingo
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Answer Set Programming: a Tour from the Basics to Advanced Development Tools and Industrial Applications
Answer Set Programming: A tour from the basics to advanced development tools and industrial applications Nicola Leone and Francesco Ricca Department of Mathematics and Computer Science, University of Calabria, Italy leone,ricca @mat.unical.it { } Abstract. Answer Set Programming (ASP) is a powerful rule-based language for knowledge representation and reasoning that has been developed in the field of logic programming and nonmonotonic reasoning. After more than twenty years from the introduction of ASP, the theoretical properties of the language are well understood and the solving technology has become mature for practical appli- cations. In this paper, we first present the basics of the ASP language, and we then concentrate on its usage for knowledge representation and reasoning in real- world contexts. In particular, we report on the development of some industry-level applications with the ASP system DLV, and we illustrate two advanced develop- ment tools for ASP, namely ASPIDE and JDLV, which speed-up and simplify the implementation of applications. 1 Introduction Answer Set Programming (ASP) [11, 19, 30] is a powerful rule-based language for knowledge representation and reasoning that has been developed in the field of logic programming and nonmonotonic reasoning. ASP features disjunction in rule heads, non monotonic negation in rule bodies [30], aggregate atoms [16] for concise mod- eling of complex combinatorial problems, and weak constraints [12] for the declarative encoding of optimization problems. Computational problems, even of high complexity [19], can be solved in ASP by specifying a logic program, i.e., a set of logic rules, such that its answer sets correspond to solutions, and then, using an answer set solver to find such solutions [38, 34]. -
Enhancing Accessibility Information in Google Maps Adding New Pieces of Information to GTFS to Improve Accessibility
SMART ACCESSIBILITY 2017 : The Second International Conference on Universal Accessibility in the Internet of Things and Smart Environments Enhancing Accessibility Information in Google Maps Adding new pieces of information to GTFS to improve accessibility Paloma Cáceres, Almudena Sierra-Alonso, Carlos E. Cuesta, José María Cavero, Belén Vela Escuela Técnica Superior de Ingeniería Informática Universidad Rey Juan Carlos, URJC Móstoles (Madrid), Spain e-mail: {paloma.caceres, almudena.sierra, carlos.cuesta, josemaria.cavero, belen.vela}@urjc.es Abstract—Google is the most important information provider validated against real data for the subway in the city of on Internet. Within the Google ecosystem, Maps is a relevant Madrid, Spain (METRO Madrid [2]). tool, which is used to calculate routes and to find points of Our proposal to specify the accessibility data of public interest. As part of this effort, it has defined Google Transit transport is based on the Identification of Fixed Objects in Feed Specification (GTFS), a format to specify data of public Public Transport (IFOPT [3]) standard, which is an extension transport. Now public transport agents can provide a “feed” of the European Reference Data Model for Public Transport complying with this specification and Google can use them and Information (Transmodel [4]) standard. IFOPT defines a represent them on Maps. In spite of their relevance for model for the main fixed objects related to access to Public accessibility in mobility, Google Maps does not offer detailed Transport, which also includes constructions to describe information about accessibility facilities to transit, and GTFS accessibility data. does not specify the necessary structure to provide that information about public transport. -
Amendments | Transportation, Economic Development And
Amend Senate S2508, Assembly A3008, AN ACT to amend the 2021 law, in relation to TED Page Line Amendment Page 4, Unnumbered line After “(Part SS);” strike out “and” 19(AN ACT CLAUSE), Page 4, Unnumbered line After “(Part TT) insert “; relating to the merger 26(AN ACT of the College Retirement Equities Fund and the CLAUSE), Teachers Insurance and Annuity Association of America; and to repeal chapter 124 of the laws of 1952 relating to the charter of the college retirement equities fund (Part UU); to amend the public authorities law, the canal law and the economic development law in relation to enacting the New York state canal system revitalization act; and to repeal article 13-A of the canal law relating to the canal recreationway commission and section 57 of the canal law relating to special conditions for leases entered prior to approval of the canal recreationway plan (Part VV); and to authorize utility and cable television assessments that provide funds to the department of health from cable tele-vision assessment revenues and to the department of agriculture and markets, department of environmental conservation, department of state, and the office of parks, recreation and historic preservation from utility assessment revenues (Part WW) Page 4, Line 4, After “through” strike out “TT” and insert “XX” Page 17, Line 3, After "§5." strike out “Paragraphs (f) and (g) of subdivision 9 of section 1209 of the public authorities law are REPEALED." and insert “The opening paragraph of subdivision 9 of section 1209 of the public authorities law is amended to read as follows: 9. -
Form W-4, Employee's Withholding Certificate
Employee’s Withholding Certificate OMB No. 1545-0074 Form W-4 ▶ (Rev. December 2020) Complete Form W-4 so that your employer can withhold the correct federal income tax from your pay. ▶ Department of the Treasury Give Form W-4 to your employer. 2021 Internal Revenue Service ▶ Your withholding is subject to review by the IRS. Step 1: (a) First name and middle initial Last name (b) Social security number Enter Address ▶ Does your name match the Personal name on your social security card? If not, to ensure you get Information City or town, state, and ZIP code credit for your earnings, contact SSA at 800-772-1213 or go to www.ssa.gov. (c) Single or Married filing separately Married filing jointly or Qualifying widow(er) Head of household (Check only if you’re unmarried and pay more than half the costs of keeping up a home for yourself and a qualifying individual.) Complete Steps 2–4 ONLY if they apply to you; otherwise, skip to Step 5. See page 2 for more information on each step, who can claim exemption from withholding, when to use the estimator at www.irs.gov/W4App, and privacy. Step 2: Complete this step if you (1) hold more than one job at a time, or (2) are married filing jointly and your spouse Multiple Jobs also works. The correct amount of withholding depends on income earned from all of these jobs. or Spouse Do only one of the following. Works (a) Use the estimator at www.irs.gov/W4App for most accurate withholding for this step (and Steps 3–4); or (b) Use the Multiple Jobs Worksheet on page 3 and enter the result in Step 4(c) below for roughly accurate withholding; or (c) If there are only two jobs total, you may check this box. -
Complexity Results for Probabilistic Answer Set Programming
International Journal of Approximate Reasoning 118 (2020) 133–154 Contents lists available at ScienceDirect International Journal of Approximate Reasoning www.elsevier.com/locate/ijar Complexity results for probabilistic answer set programming ∗ Denis Deratani Mauá a, , Fabio Gagliardi Cozman b a Institute of Mathematics and Statistics, Universidade de São Paulo, Brazil b Escola Politécnica, Universidade de São Paulo, Brazil a r t i c l e i n f o a b s t r a c t Article history: We analyze the computational complexity of probabilistic logic programming with Received 16 May 2019 constraints, disjunctive heads, and aggregates such as sum and max. We consider Received in revised form 25 October 2019 propositional programs and relational programs with bounded-arity predicates, and look Accepted 9 December 2019 at cautious reasoning (i.e., computing the smallest probability of an atom over all Available online 16 December 2019 probability models), cautious explanation (i.e., finding an interpretation that maximizes the Keywords: lower probability of evidence) and cautious maximum-a-posteriori (i.e., finding a partial Probabilistic logic programming interpretation for a set of atoms that maximizes their lower probability conditional on Answer set programming evidence) under Lukasiewicz’s credal semantics. Computational complexity © 2019 Elsevier Inc. All rights reserved. 1. Introduction Probabilities and logic programming have been combined in a variety of ways [1–8]. A particularly interesting and power- ful combination is offered by probabilistic answer set programming, which exploits the powerful knowledge representation and problem solving toolset of answer set programming [9]. Available surveys describe probabilistic logic programming in detail and go over many promising applications [10–13]. -
Answer Set Programming: a Primer?
Answer Set Programming: A Primer? Thomas Eiter1, Giovambattista Ianni2, and Thomas Krennwallner1 1 Institut fur¨ Informationssysteme, Technische Universitat¨ Wien Favoritenstraße 9-11, A-1040 Vienna, Austria feiter,[email protected] 2 Dipartimento di Matematica, Universita´ della Calabria, I-87036 Rende (CS), Italy [email protected] Abstract. Answer Set Programming (ASP) is a declarative problem solving para- digm, rooted in Logic Programming and Nonmonotonic Reasoning, which has been gaining increasing attention during the last years. This article is a gentle introduction to the subject; it starts with motivation and follows the historical development of the challenge of defining a semantics for logic programs with negation. It looks into positive programs over stratified programs to arbitrary programs, and then proceeds to extensions with two kinds of negation (named weak and strong negation), and disjunction in rule heads. The second part then considers the ASP paradigm itself, and describes the basic idea. It shows some programming techniques and briefly overviews Answer Set solvers. The third part is devoted to ASP in the context of the Semantic Web, presenting some formalisms and mentioning some applications in this area. The article concludes with issues of current and future ASP research. 1 Introduction Over the the last years, Answer Set Programming (ASP) [1–5] has emerged as a declar- ative problem solving paradigm that has its roots in Logic Programming and Non- monotonic Reasoning. This particular way of programming, in a language which is sometimes called AnsProlog (or simply A-Prolog) [6, 7], is well-suited for modeling and (automatically) solving problems which involve common sense reasoning: it has been fruitfully applied to a range of applications (for more details, see Section 6). -
SQL*Plus User's Guide and Reference Release 8.1.6
SQL*Plus® User’s Guide and Reference Release 8.1.6 October, 1999 Part No. A75664-01 SQL*Plus User’s Guide and Reference, Release 8.1.6 Part No. A75664-01 Copyright © 1996, 1999, Oracle Corporation. All rights reserved. Contributing Authors: Larry Baer, Lisa Colston, Roland Kovacs, Karen Denchfield-Masterson, Alison Holloway, Sanjeev Jhala, Christopher Jones, Anita Lam, Nimish Mehta, Luan Nim, Bud Osterberg, Irene Paradisis, Richard Rendell, Frank Rovitto, Farokh Shapoorjee, Larry Stevens, Andre Touma, Simon Watt The Programs (which include both the software and documentation) contain proprietary information of Oracle Corporation; they are provided under a license agreement containing restrictions on use and disclosure and are also protected by copyright, patent, and other intellectual and industrial property laws. Reverse engineering, disassembly, or decompilation of the Programs is prohibited. The information contained in this document is subject to change without notice. If you find any problems in the documentation, please report them to us in writing. Oracle Corporation does not warrant that this document is error free. Except as may be expressly permitted in your license agreement for these Programs, no part of these Programs may be reproduced or transmitted in any form or by any means, electronic or mechanical, for any purpose, without the express written permission of Oracle Corporation. If the Programs are delivered to the U.S. Government or anyone licensing or using the programs on behalf of the U.S. Government, the following notice is applicable: Restricted Rights Notice Programs delivered subject to the DOD FAR Supplement are "commercial computer software" and use, duplication, and disclosure of the Programs including documentation, shall be subject to the licensing restrictions set forth in the applicable Oracle license agreement. -
Answer Set Programming
ANSWER SET PROGRAMMING Tran Cao Son Department of Computer Science New Mexico State University Las Cruces, NM 88011, USA [email protected] http://www.cs.nmsu.edu/~tson October 2005 Answer Set Programming. Acknowledgement This tutorial contains some materials from tutorials on answer set programming and on knowledge representation and logic programming from those provided by • Chitta Baral, available at www.public.asu.edu/~cbaral. • Michael Gelfond, available at www.cs.ttu.ued/~mgelfond. Tran Cao Son 1 Answer Set Programming. Introduction — Answer Set Programming Answer set programming is a new programming paradigm. It is introduced in the late 90’s and manages to attracts the intention of different groups of researchers thanks to its: • declarativeness: programs do not specify how answers are computed; • modularity: programs can be developed incrementally; • expressiveness: answer set programming can be used to solve problems in high 2 complexity classes (e.g. ΣP , Π2P , etc.) Answer set programming has been applied in several areas: reasoning about actions and changes, planning, configuration, wire routing, phylogenetic inference, semantic web, information integration, etc. Tran Cao Son 2 Answer Set Programming. Purpose • Introduce answer set programming • Provide you with some initial references, just in case • ...you get excited about answer set programming Tran Cao Son 3 Answer Set Programming. Outline • Foundation of answer set programming: logic programming with answer set semantics (syntax, semantics, early application). • Answer set programming: general ideas and examples • Application of answer set programming in – Knowledge representation – Constraint satisfaction problem – Combinatoric problems – Reasoning about action and change – Planning and diagnostic reasoning • Current issues Tran Cao Son 4 LOGIC PROGRAMMING AND ANSWER SET SEMANTICS Answer Set Programming. -
A Meta-Programming Technique for Debugging Answer-Set Programs∗
A Meta-Programming Technique for Debugging Answer-Set Programs∗ Martin Gebser1, Jorg¨ Puhrer¨ 2, Torsten Schaub1, and Hans Tompits2 1 Institut fur¨ Informatik, Universitat¨ Potsdam, Germany, {gebser,torsten}@cs.uni-potsdam.de 2 Institut fur¨ Informationssysteme 184/3, Technische Universitat¨ Wien, Austria, {puehrer,tompits}@kr.tuwien.ac.at Abstract applying such an approach to ASP results in some deci- sive drawbacks, undermining the declarativity of answer- Answer-set programming (ASP) is widely recognised as a vi- able tool for declarative problem solving. However, there is set semantics. In particular, establishing canonical tracing- currently a lack of tools for developing answer-set programs. based techniques for debugging answer-set programs re- In particular, providing tools for debugging answer-set pro- quires also a canonical procedure for answer-set computa- grams has recently been identified as a crucial prerequisite tion, and programmers would have to be familiar with the al- for a wider acceptance of ASP. In this paper, we introduce a gorithm. This would lead to a shift of perspectives in which meta-programming technique for debugging in ASP. The ba- an answer-set program is degraded from a declarative prob- sic question we address is why interpretations expected to be lem description to a set of parameters for a static solving answer sets are not answer sets of the program to debug. We algorithm. Therefore, we argue for declarative debugging thus deal with finding semantical errors of programs. The ex- strategies that are independent of answer-set computation. planations provided by our method are based on an intuitive Indeed, among the few approaches dealing with debug- scheme of errors that relies on a recent characterisation of the answer-set semantics. -
Floating Slab Mats 2020
PRODUCT REFERENCE LIST Floating Slab Mats 2020 Year Network Project Product Type Type Track Load Total 2002 FR TBM Bordeaux: Tramway - Tramway 100 kN 31,000 m² Bordeaux 2002 PT Metro Lisbon: Odivelas, - Metro 100 kN 10,000 m² Lisboa Campo Grande & Falagueira station 2003 BE MIVB/STIB Brussels: Chaussée de - Tramway 100 kN 1,800 m² Charleroi - Phase 1 2003 Brussels: Chaussée de - Tramway 100 kN 5,250 m² Charleroi - Phase 2 2003 De Lijn Gent: Gent St-Pieters - - Tramway 100 kN 10,000 m² Flanders Expo 2003 FR TBM Bordeaux: Tramway - Tramway 130 kN 9,700 m² Bordeaux 2003 GR TRAM SA Athens: Kasamouli - - Tramway 100 kN 4,000 m² Panagitsas 2004 BE De Lijn Gent: Gent St-Pieters - - Tramway 95 kN 400 m² Flanders Expo 2004 ES GTP-FGV Valencia: Tram Valencia - Tramway 113 kN 200 m² 2005 BE MIVB/STIB Brussels: Avenue de - Tramway 100 kN 2,245 m² l'Hippodrome 2005 Brussels: Rue du Bailli - Tramway 100 kN 2,410 m² 2005 Brussels: Avenue - Tramway 100 kN 610 m² P.Janson 2005 Brussels: L94 - - Tramway 120 kN 600 m² Boulevard du Souverain 2005 Brussels: Montgomery - Tramway 100 kN 250 m² 2005 Brussels: Terminus - Tramway 100 kN 550 m² Boondael 2005 PT Metro Porto Porto: Metro do Porto - Tramway 100 kN 3,900 m² 2006 BE MIVB/STIB Brussels: Terminus - Tramway 130 kN 481 m² Louise Legrand 2006 Brussels: Montgomery - Tramway 100 kN 300 m² Fase 2 2006 Brussels: Montgomery - Tramway 100 kN 290 m² Fase 2E 2006 Brussels: Wielemans - - Tramway 100 kN 15 m² Van Volxem 2006 ES GTP-FGV Alicante: Tram Line 2 PANDROL FSM- Tramway 113 kN 690 m² L10 2020 © Pandrol 2020 -
Survival Guide Athens Madrid Upm November 2018
UPM Athens Programme November 2018 SURVIVAL GUIDE ATHENS MADRID UPM NOVEMBER 2018 1 UPM Athens Programme November 2018 1. MUST DO & MUST HAVE · GROUPS Join our FB and WA groups asap! There we may help and warn you about any changes, if necessary. Facebook Group: https://www.facebook.com/groups/1112150795609983/ WhatsApp Group: https://chat.whatsapp.com/KxEQBfwqSnC0ACcgxouOEZ · EMERGENCY NUMBERS There are some emergency contact phone numbers: Organiser Victor: +34 692 59 41 46 Organiser Natalia: +34 608 98 91 44 Health insurance: We’d like to remember you that it’s a must to travel with your European Health Insurance Card and/or a health insurance. If you have your own private health insurance it is really important that you know the terms of your contract when going abroad. · METRO One of the best ways to travel through Madrid is the Metro which is a rail system. It operates every day from 6:00 AM until 1:30 AM and the trais pass every few minutes, so it is quite a quick way to get everywhere in Madrid. There is a Metro Map which we highly recommend you to download: Metro Map: https://www.metromadrid.es/export/sites/metro/comun/documentos/planos/Planoesquema ticoingles.pdf Take a look at the webpage of the Metro. You may find it very useful, as in this page you can enter two metro stations and it tells you how to get from one station to other, which trains you have to take and the time it will take you yo get there. In this webpage you will also find the prices of the tickets and where to buy them. -
Integrating Answer Set Programming and Constraint Logic Programming
Integrating Answer Set Programming and Constraint Logic Programming Veena S. Mellarkod and Michael Gelfond and Yuanlin Zhang {veena.s.mellarkod,mgelfond,yzhang}@cs.ttu.edu Texas Tech University Dedicated to Victor Marek on his 65th birthday as a specification for the sets of beliefs to be held by a ra- tional reasoner associated with Π. Such sets, called an- Abstract swer sets of Π, are represented by collections of ground literals. A rule (1) is viewed as a constraint which says We introduce a knowledge representation language that if literals lk+1, . , ln belong to an answer set A of AC(C) extending the syntax and semantics of ASP Π and none of the literals ln+1, . , lm belong to A then and CR-Prolog, give some examples of its use, and A must contain at least one of the literals l , . , l . To present an algorithm, ACsolver, for computing answer 1 k sets of AC(C) programs. The algorithm does not re- form answer sets of Π, the reasoner must satisfy Π’s quire full grounding of a program and combines “clas- rules together with the rationality principle which says: sical” ASP solving methods with constraint logic pro- “Believe nothing you are not forced to believe”. gramming techniques and CR-Prolog based abduction. The AC(C) based approach often allows to solve prob- Given a computational problem P , an ASP programmer lems which are impossible to solve by more traditional • Expresses information relevant to the problem in the ASP solving techniques. We belief that further inves- language of ASP; tigation of the language and development of more effi- cient and reliable solvers for its programs can help to • Reduces P to a query Q requesting computation of substantially expand the domain of applicability of the (parts of) answer sets of Π.