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Qualitative Reasoning

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Abstract

In this chapter, we discuss two research areas related to qualitative reasoning: firstly, qualitative reasoning about dynamical systems, or qualitative physics, that aims at providing qualitative descriptions of processes in the sense that they are characterized regardless of quantitative data (for instance, “the tank overflows”, “temperature increases”, etc.); and secondly qualitative spatial and temporal reasoning (QSTR), that aims at describing and reasoning about qualitative relationships between spatial regions (“the stadium is on the island”, “the bike path crosses the river”) or between time periods (“the minister’s visit preceded the opening of the Olympic Games”).

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Notes

  1. 1.

    MONET: Network of Excellence on Model Based Systems and Qualitative Reasoning.

  2. 2.

    \(\mathsf {DC}\) stands for disconnected, \(\mathsf {EC}\) for externally connected, \(\mathsf {PO}\) for partial overlap, \(\mathsf {TPP}\) for tangential proper part and \(\mathsf {NTPP}\) for non-tangential proper part; \(\mathsf {TPPI}\) and \(\mathsf {NTPPI}\) are the converses of \(\mathsf {TPP}\) and \(\mathsf {NTPP}\), respectively.

  3. 3.

    Those calculi divide all directions in the plane with respect to a given point of reference into a finite number of sectors with a given angle; Freksa’s calculus is the case where the angles are right angles, the Flip-flop calculus where they are 180\(^{\circ }\) angles.

  4. 4.

    This was already the case for several calculi in the literature, such as Vilain’s Point-and-Interval calculus (Vilain 1982), and more generally Ligozat’s \(\mathbf {A}_{S}\) calculi, where S is a set of positive integers with more than one element (Ligozat 1991).

  5. 5.

    i.e. Subnetworks for which all constraints are basic relations.

  6. 6.

    This preposition roughly corresponds to the English preposition on.

  7. 7.

    French National Institute for Agronomic Research.

  8. 8.

    See for example the RACER tool: http://www.racer-systems.com/.

References

  • Accary-Barbier T., Calabretto S. (2008) Building and using temporal knowledge in archaeological documentation. J. Intell. Inf. Syst. 31:147–159

    Google Scholar 

  • Afsordegan A., Sánchez M., Agell N., Aguado J. C., Gamboa G. (2016) Absolute order-of-magnitude reasoning applied to a social multi-criteria evaluation framework. J. Exp. Theor. Artif. Intell. 28(1–2):261–274

    Google Scholar 

  • Aiello M., Pratt-Hartmann I., van Benthem J. (eds.) (2007a) Handbook of spatial logics. Springer, Netherlands

    Google Scholar 

  • Aiello M., Pratt-Hartmann I., van Benthem J. (2007b)What is spatial logic? In [Aiello et al. 2007a], pp 1–11

    Google Scholar 

  • Alboody A., Sedes F., Inglada J. (2010) Fuzzy intersection and difference model for topological relations. In: IFSA-EUSFLAT 2009 Proceedings, pp 1–6

    Google Scholar 

  • Allen J. F. (1983) Maintaining knowledge about temporal intervals. Commun. ACM 26(11):832–843

    Google Scholar 

  • Amaneddine N., Condotta J.-F., Sioutis M. (2013) Efficient approach to solve the minimal labeling problem of temporal and spatial qualitative constraints. In: Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI’13), Beijing, China, 3–9 August 2013, pp 696–702

    Google Scholar 

  • Atif J., Hudelot C., Fouquier G., Bloch I., Angelini E. (2007) From generic knowledge to specific reasoning for medical image interpretation using graph-based representations. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI’07), pp 224–229

    Google Scholar 

  • Aurnague M., Vieu L., Borillo A. (1997) Représentation formelle des concepts spatiaux dans la langue. In: Denis M (ed) Langage et cognition spatiale. Masson, pp 69–102

    Google Scholar 

  • Balbiani P., Condotta J.-F. (2002) Computational complexity of propositional linear temporal logics based on qualitative spatial or temporal reasoning. In: Proceedings of the 4th international workshop on frontiers of combining systems (FroCoS 2002). LNCS, vol 2309, pp 162–176

    Google Scholar 

  • Balbiani P., Condotta J.-F., Fariñas del Cerro L. (1998) A model for reasoning about bidimensional temporal relations. In: Proceedings of KR-98, pp 124–130

    Google Scholar 

  • Balbiani P., Condotta J-F., Ligozat G. (2006) On the consistency problem for the INDU calculus. J. Appl. Log. 4:119–140

    Google Scholar 

  • Balbiani P., Osmani A. (2000) A model for reasoning about topological relations between cyclic intervals. In: Proceedings of KR-2000, Breckenridge, Colorado, pp 378–385

    Google Scholar 

  • Barkowsky T., Knauff M., Ligozat G., Montello D. R. (eds.) (2008) Spatial cognition V: Reasoning, Action, Interaction. International Conference on Spatial Cognition 2006, Bremen, Germany, 24–28 September 2006, revised selected papers. Lecture notes in computer science, vol 4387. Springer, Berlin

    Google Scholar 

  • Bedel O., Ferré S., Ridoux O., Quesseveur E. (2008) GEOLIS: a logical information system for geographical data. Revue Internationale de Géomatique 17(3–4):371–390

    Google Scholar 

  • Ben-Naim J., Benferhat S., Papini O., Würbel E. (2004) An answer set programming encoding of prioritized removed sets revision: application to GIS. In: Alferes JJ, Leite JA (eds) JELIA, vol 3229. Lecture notes in computer science. Springer, Berlin, pp 604–616

    Google Scholar 

  • Benferhat S., Ben-Naim J., Papini O., Würbel E. (2010) An answer set programming encoding of prioritized removed sets revision: application to GIS. Appl. Intell. 32(1):60–87

    Google Scholar 

  • Bestougeff H., Ligozat G. (1992) Logical tools for temporal knowledge representation. Ellis Horwood, New York

    Google Scholar 

  • Bettini C., Jajodia S., Wang S. X. (2000) Time granularities in databases, data mining and temporal reasoning. Springer, Berlin

    Google Scholar 

  • Bettini C., Wang X. S., Jajodia S. (2002) Solving multi-granularity temporal constraint networks. Artif. Intell. 140:107–152

    Google Scholar 

  • Billen R., Clementini E. (2004) A model for ternary projective relations between regions. In: Bertino E., Christodoulakis S., Plexousakis D., Christophides V., Koubarakis M., Böhm K., Ferrari E. (eds) EDBT, vol 2992. Lecture notes in computer science. Springer, Berlin, pp 310–328

    Google Scholar 

  • Bloch I. (1999) Fuzzy relative position between objects in image processing: a morphological approach. IEEE Trans. Pattern Anal. Mach. 21(7):657–664

    Google Scholar 

  • Bloch I. (2005) Fuzzy spatial relationships for image processing and interpretation: a review. Image Vis. Comput. 23(2):89–110

    Google Scholar 

  • Boutilier C. (ed.) (2009) IJCAI 2009 proceedings of the 21st International Joint Conference on Artificial Intelligence, Pasadena, California, USA, 11–17 July 2009

    Google Scholar 

  • Bratko I., Suc D. (2003) Learning qualitative models. AI Mag. 24(4):107–119

    Google Scholar 

  • Bredeweg B., Forbus K. (2003) Qualitative modeling in education. AI Mag. 24(4):35–46

    Google Scholar 

  • Bredeweg B., Liem J., Beek W., Linnebank F., Gracia J., Lozano E., Wißner M., Bühling R., Salles P., Noble R et al. (2013) Dynalearn - an intelligent learning environment for learning conceptual knowledge. AI Mag. 34(4):46–65

    Google Scholar 

  • Bredeweg B., Linnebank F., Bouwer A., Liem J. (2009) Garp3 workbench for qualitative modelling and simulation. Ecol. Inform. 4(5–6):263–281

    Google Scholar 

  • Bredeweg B., Struss P. (2003) Current topics in qualitative reasoning. AI Mag. 24(4):13–16

    Google Scholar 

  • Cascio F., Console L., Guagliumi M., Osella M., Panati A., Sottano S., Dupré D. (1999) Generating on-board diagnostics of dynamic automotive systems based on qualitative models [1]. AI Commun. 12(1–2):43–51

    Google Scholar 

  • Chaudet H. (2006) Extending the event calculus for tracking epidemic spread. Artif. Intell. Med. 38(2):137–156. Special issue on Temporal Representation and Reasoning in medicine

    Google Scholar 

  • Chen J., Cohn A. G., Liu D., Wang S., Ouyang J., Yu Q. (2015) A survey of qualitative spatial representations. Knowl. Eng. Rev. 30(1):106–136

    Google Scholar 

  • Chevriaux Y., Saux E., Claramunt C. (2005) A landform-based approach for the representation of terrain silhouettes. In: Shahabi C., Boucelma O. (eds.) GIS. ACM, pp 260–266

    Google Scholar 

  • Cohen-Solal Q., Bouzid M., Niveau A. (2015) An algebra of granular temporal relations for qualitative reasoning. In: Twenty-fourth International Joint Conference on Artificial Intelligence, IJCAI 2015

    Google Scholar 

  • Cohen-Solal Q., Bouzid M., Niveau A. (2017a) Checking the consistency of combined qualitative constraint networks. In: AAAI, pp 1084–1090

    Google Scholar 

  • Cohen-Solal Q., Bouzid M., Niveau A. (2017b) Temporal sequences of qualitative information: reasoning about the topology of constant-size moving regions. Twenty-sixth International Joint Conference on Artificial Intelligence IJCAI 2017:986–992

    Google Scholar 

  • Cohn A., Li S., Liu W., Renz J. (2014) Reasoning about topological and cardinal direction relations between 2-dimensional spatial objects. J. Artif. Intell. Res. (JAIR) 51:493–532

    Google Scholar 

  • Condotta J.-F., D’Almeida D. (2011) Consistency of qualitative constraint networks from tree decompositions. In: Combi C., Leucker M., Wolter F. (eds.) Proceedings of the 18th international symposium on temporal representation an reasoning (TIME’11), Lübeck, Germany, pp 149–156

    Google Scholar 

  • Condotta J.-F., Kaci S., Schwind N. (2009) Merging qualitative constraint networks defined on different qualitative formalisms. In: Hornsby K. S., Claramunt C., Denis M., Ligozat G. (eds) COSIT. Lecture notes in computer science, vol 5756. Springer, Berlin, pp 106–123

    Google Scholar 

  • Condotta J.-F., Ligozat G. (2004) Axiomatizing the cyclic interval calculus. In: Proceedings of KR’2004, pp 95–105

    Google Scholar 

  • Condotta J-F., Ligozat G., Saade M. (2006a) A generic toolkit for n-ary qualitative temporal and spatial calculi. The 13th International Symposium on Temporal Representation and Reasoning (TIME’06). Budapest, Hungary, pp 78–86

    Google Scholar 

  • Condotta J.-F., Ligozat G., Saade M., Tripakis S. (2006b) Ultimately periodic simple temporal problems (UPSTPs). In: MOI (ed.) Time. IEEE Computer Society, pp 69–77

    Google Scholar 

  • Condotta J-F., Ligozat G., Tripakis S.(2005) Ultimately periodic qualitative constraint networks for spatial and temporal reasoning. ICTAI. IEEE Computer Society 584–588

    Google Scholar 

  • Condotta J.-F., Nouaouri I., Sioutis M. (2016) A SAT approach for maximizing satisfiability in qualitative spatial and temporal constraint networks. In: Baral C., Delgrande J.P., Wolter F. (eds). Principles of knowledge representation and reasoning: Proceedings of the Fifteenth International Conference, KR 2016, Cape Town, South Africa, 25–29 April 2016. AAAI, pp 432–442

    Google Scholar 

  • Cotteret G. (2005). Extraction d’éléments curvilignes guidée par des mécanismes attentionnels pour des images de télédétection : approche par fusion de données. PhD thesis, Université Paris-Sud, France

    Google Scholar 

  • Dague P. (1993a) Numeric reasoning with relative orders of magnitude. In: Proceedings of the National Conference on Artificial Intelligence, pp 541-547

    Google Scholar 

  • Dague P. (1993b) Symbolic reasoning with relative orders of magnitude. In: Proceedings of the International Joint Conference on Artificial Intelligence, vol 13. Lawrence Erlbaum Associates Ltd, USA, p 1509

    Google Scholar 

  • Dague P. (1995) Qualitative reasoning: a survey of techniques and applications. AI Communications 8(3/4):119–192

    Google Scholar 

  • Dague P., Travé-Massuyès L. (2004) Raisonnement causal en physique qualitative. Intellectica. 38:247–290

    Google Scholar 

  • Dauphin-Tanguy G et al. (2000) Les bond graphs. Hermès Science, Paris

    Google Scholar 

  • de Beuvron F. D. B., Marc-Zwecker S., Zanni-Merk C., Le Ber F. (2015) Combining ontological and qualitative spatial reasoning: application to urban images interpretation. In: Proceedings of the International Joint Conference on Knowledge Discovery, Knowledge Engineering, and Knowledge Management (IC3K (2013) CCIS, vol 454. Springer, Berlin, pp 182–198

    Google Scholar 

  • de Jong H., Geiselmann J., Hernandez C., Page M. (2003) Genetic network analyzer: qualitative simulation of genetic regulatory networks. Bioinformatics 19(3):336–344

    Google Scholar 

  • de Kleer J. (1977) Multiple representations of knowledge in a mechanics problem-solver. In: Proceedings of the 5th International Joint Conference on Artificial Intelligence. Morgan Kaufmann, USA, pp 299–304

    Google Scholar 

  • de Kleer J. (1979) Causal and teleological reasoning in circuit recognition. Massachusetts Institute of Technology, Cambridge

    Google Scholar 

  • de Kleer J., Brown J. (1984) A qualitative physics based on confluences. Artif. Intell. 24(1–3):7–83

    Google Scholar 

  • de Kleer J., Brown J. (1986) Theories of causal ordering. Artif. Intell. 29(1):33–61

    Google Scholar 

  • de Koning K., Bredeweg B., Breuker J., Wielinga B. (2000) Model-based reasoning about learner behaviour. Artif. Intell. 117(2):173–229

    Google Scholar 

  • Dylla F., Mossakowski T., Schneider T., Wolter D. (2013) Algebraic properties of qualitative spatio-temporal calculi. In: Spatial Information Theory, proceedings of COSIT-13. Springer, Berlin, pp 516–536

    Google Scholar 

  • Egenhofer M. J. (1989) A formal definition of binary topological relationships. In: Litwin W., Schek H.-J. (eds) FODO. Lecture notes in computer science, vol 367. Springer, Berlin, pp 457–472

    Google Scholar 

  • Egenhofer M. J. (1991) Reasoning about binary topological relations. Lecture notes in computer science 525:143–160

    Google Scholar 

  • Euzenat J. (1996) An algebraic approach for granularity in qualitative space and time representation. In: IJCAI-95, pp 894–900

    Google Scholar 

  • Euzenat J. (2001) Granularity in relational formalisms with application to time and space. Comput. Intell. 17(4):703–737

    Google Scholar 

  • Euzenat J. (2008) Algebras of ontology alignment relations. Springer, Berlin

    Google Scholar 

  • Euzenat J., Montanari A. (2005) Time granularity. Handbook of temporal reasoning in Artificial Intelligence, Chapter time granularity. Elsevier, Amsterdam, pp 59–118

    Google Scholar 

  • Falkenhainer B., Forbus Dedre K. (1989) The structure-mapping engine: algorithm and examples. Artif. Intell. 41(1):1–63

    Google Scholar 

  • Forbus K. (1984) Qualitative process theory. Artif. Intell. 24(1–3):85–168

    Google Scholar 

  • Forbus K., Mostek T., Ferguson R. (2002) An analogy ontology for integrating analogical processing and first-principles reasoning. In: Proceedings of the National Conference on Artificial Intelligence, pp 878–885

    Google Scholar 

  • Forbus K. D. (2014) Qualitative reasoning about space and motion. Mental models. Psychology, UK, pp 61–82

    Google Scholar 

  • Freksa C. (1992) Using orientation information for qualitative spatial reasoning. In: Frank A. U., Campari I., Formentini U. (eds) Spatio-temporal reasoning. Lecture notes in computer science, vol 639. Springer, Berlin, pp 162–178

    Google Scholar 

  • Ganter B., Wille R. (1999) Formal concept analysis. Springer, Berlin

    Google Scholar 

  • Gantner Z., Westphal M., Wölfl S. (2008) GQR- a fast reasoner for binary qualitative constraint calculi. In: Proceedings of the AAAI’08 workshop on Spatial and Temporal Reasoning, Chicago, USA

    Google Scholar 

  • Gerevini A., Nebel B. (2002) Qualitative spatio-temporal reasoning with RCC-8 and Allen’s interval calculus: computational complexity. In: van Harmelen F. (ed.) Proceedings of ECAI 2002. IOS, pp 312–316

    Google Scholar 

  • Gerevini A., Renz J. (2002) Combining topological and size information for spatial reasoning. Artif. Intell. 137(1–2):1–42

    Google Scholar 

  • Ghallab M., Alaoui A. M. (1989) Managing efficiently temporal relations through indexed spanning trees. In: IJCAI, pp 1297–1303

    Google Scholar 

  • Goyal R. K., Egenhofer M. J. (1997) The direction-relation matrix: a representation for directions relations between extended spatial objects. In: The annual assembly and the summer retreat of University Consortium for geographic information systems science, Bar Harbor, ME

    Google Scholar 

  • Guerrin F. (1991) Qualitative reasoning about an ecological process: interpretation in hydroecology. Ecol. Model. 59(3–4):165–201

    Google Scholar 

  • Güsgen H. (1989) Spatial reasoning based on Allen’s temporal logic. Technical report TR-89-049, ICSI, Berkeley, CA

    Google Scholar 

  • Hayes P. (1979) The naive physics manifesto. Expert systems in the microelectronic age 242–270

    Google Scholar 

  • Hayes P. (1985) The second naive physics manifesto. In: Hobbs J., Moore R. (eds.) Formal theories of the commonsense world, pp 1-36

    Google Scholar 

  • Hobbs J. R. (1985) Granularity. In: Proceedings of IJCAI-85, pp 432–435

    Google Scholar 

  • Hofer B., Nica I., Wotawa F. (2017) Qualitative deviation models versus quantitative models for fault localization in spreadsheets. In: 30th International Workshop on Qualitative Reasoning (QR), IJCAI 2017, Melbourne, Australia

    Google Scholar 

  • Inants A. (2016) Qualitative calculi with heterogeneous universes. PhD thesis, Grenoble Alpes University, France

    Google Scholar 

  • Ironi L., Panzeri L., Plahte E. (2008) An algorithm for qualitative simulation of gene regulatory networks with steep sigmoidal response functions. Algebraic biology, pp 110–124

    Google Scholar 

  • Ironi L., Tentoni S. (2007) Automated detection of qualitative spatio-temporal features in electrocardiac activation maps. Artif. Intell. Med. 39(2):99–111

    Google Scholar 

  • Iwasaki Y. (1997) Real-world applications of qualitative reasoning. IEEE Expert Intell. Syst. Appl. 12(3):16–21 Special issue

    Google Scholar 

  • Iwasaki Y., Simon H. (1986) Causality in device behavior. Artif. Intell. 29(1):3–32

    Google Scholar 

  • Iwasaki Y., Simon H. (1994) Causality and model abstraction. Artif. Intell. 67(1):143–194

    Google Scholar 

  • Jeansoulin R., Papini O. (2007) Underwater archaeological knowledge analysis and representation in the VENUS project: a preliminary draft. In: Georgopoulos A. (ed) XXI international CIPA symposium. The international archives of photogrammetry, remote sensing and spatial information sciences, vol XXXVI-5/C53. ICOMOS/ISPRS Committee for Documentation of Cultural Heritage, pp 394–399

    Google Scholar 

  • Jonsson P., Bäckström C. (1998) A unifying approach to temporal constraint reasoning. Artif. Intell. 102(1):143–155

    Google Scholar 

  • Kansou K., Bredeweg B. (2014) Hypothesis assessment with qualitative reasoning: modelling the Fontestorbes fountain. Ecol. Inform. 19:71–89

    Google Scholar 

  • Khatib L. (1994) Reasoning with non-convex time intervals. PhD thesis, Florida Institute of Technology, Melbourne, Florida

    Google Scholar 

  • Koubarakis M. (1996) Tractable disjunctions of linear constraints. In: Freuder, E. C. (ed.) CP. Lecture notes in computer science, vol 1118. Springer, Berlin, pp 297–307

    Google Scholar 

  • Koubarakis M. (2001) Tractable disjunctions of linear constraints: basic results and applications to temporal reasoning. Theor. Comput. Sci. 266(1–2):311–339

    Google Scholar 

  • Kuipers B. (1985) The limits of qualitative simulation. In: Proceedings of the 9th International Joint Conference on Artificial Intelligence. Morgan Kaufmann, USA, pp 128–136

    Google Scholar 

  • Kuipers B. (1986) Qualitative simulation. Artif. Intell. 29(3):289–338

    Google Scholar 

  • Kuipers B. (1994) Qualitative reasoning: modeling and simulation with incomplete knowledge. MIT, Cambridge

    Google Scholar 

  • Lancaster K. (1965) The theory of qualitative linear systems. Econometrica: J of the Econometric Society 33(2):395–408

    Google Scholar 

  • Lascarides A., Asher N. (1991) Discourse relations and defeasible knowledge. In: ACL, pp 55–62

    Google Scholar 

  • Lascarides A., Asher N. (1993) Temporal interpretation, discourse relations, and commonsense entailment. Linguistics and Philosophy 16:437–493

    Google Scholar 

  • Le Ber F., Ligozat G., Papini O. (eds) (2007) Raisonnements sur l’espace et le temps. Hermès / Lavoisier, Paris

    Google Scholar 

  • Le Ber F., Napoli A. (2003) Design and comparison of lattices of topological relations for spatial representation and reasoning. J. Exp. Theor. Artif. Intell. 15(3):331–371

    Google Scholar 

  • Le Ber F., Napoli A., Metzger J-L., Lardon S. (2003) Modeling and comparing farm maps using graphs and case-based reasoning. J. Univers. Comput. Sci. 9(9):1073–1095

    Google Scholar 

  • Levesque H., Brachman R. (1985) A fundamental tradeoff in knowledge representation and reasoning. In: Brachman R. J., Levesque H. (eds) Knowledge representation and reasoning. Morgan Kaufmann, Stanford

    Google Scholar 

  • Li H, Mu\(\tilde{\text{n}}\)oz-Avila H., Bransen D., Hogg C., Alonso R. (2009a) Spatial event prediction by combining value function approximation and case-based reasoning. In: McGinty L., Wilson D. (eds) ICCBR, (2009) LNAI 5650. Springer, Berlin, pp 465–478

    Google Scholar 

  • Li J. J, Huang J., Renz J. (2009b) A divide-and-conquer approach for solving interval algebra networks. In [Boutilier 2009], pp 572–577

    Google Scholar 

  • Li S., Ying M. (2003) Region connection calculus: its models and composition table. Artif. Intell. 145(1–2):121–146

    Google Scholar 

  • Ligozat G. (1990) Weak representations of interval algebras. In: Proceedings of AAAI-90, pp 715–720

    Google Scholar 

  • Ligozat G. (1991) On generalized interval calculi. In: Proceedings of AAAI-91, pp 234–240

    Google Scholar 

  • Ligozat G. (1993) Qualitative triangulation for spatial reasoning. In: Frank A. U., Campari I. (eds) Spatial information theory (COSIT’93). LNCS, vol 716. Springer, Berlin, pp 54–68

    Google Scholar 

  • Ligozat G. (1994) Tractable relations in temporal reasoning: pre-convex relations. In: Anger F. D., Güsgen H., Ligozat G. (eds) Proceedings of the ECAI-94 workshop on Spatial and Temporal Reasoning, Amsterdam, pp 99–108

    Google Scholar 

  • Ligozat G. (1996) A new proof of tractability for ORD-Horn relations. In: Proceedings of AAAI-96, pp 395–401

    Google Scholar 

  • Ligozat G. (2001) When tables tell it all. In: Montello D. R. (ed) COSIT. Lecture notes in computer science, vol 2205. Springer, Berlin, pp 60–75

    Google Scholar 

  • Ligozat G. (2013) Qualitative spatial and temporal reasoning. Wiley, New Jersey

    Google Scholar 

  • Ligozat G., Nowak J., Schmitt D. (2007) From language to pictorial representations. In: Vetulani Z. (ed) Proceedings of the Language and Technology Conference (L&TC’07), Poznań, Poland. Wydawnictwo Poznańskie

    Google Scholar 

  • Ligozat G., Renz J. (2004) What is a qualitative calculus? a general framework. In: Proceedings of PRICAI’04, LNCS 3157, New Zealand, Auckland, pp 53–64

    Google Scholar 

  • Ligozat G., Vetulani Z., Osiński J. (2011) Spatiotemporal aspects of the monitoring of complex events for public security purposes. Spat. Cogn. Comput. 11(1):103–128

    Google Scholar 

  • Liu W., Li S. (2012) Solving minimal constraint networks in qualitative spatial and temporal reasoning. In: Principles and practice of constraint programming - 18th international conference, CP 2012, Québec City, Canada, 8–12 October 2012, Proceedings, pp 464–479

    Google Scholar 

  • Liu W., Li S., Renz J. (2009) Combining RCC-8 with qualitative direction calculi: algorithms and complexity. In [Boutilier 2009], pp 854–859

    Google Scholar 

  • Long Z., Li S. (2015) On distributive subalgebras of qualitative spatial and temporal calculi. In: Spatial Information Theory - 12th International Conference, COSIT 2015, Santa Fe, NM, USA, 12–16 October 2015, Proceedings, pp 354–374

    Google Scholar 

  • Loustau P., Nodenot T., Gaio M. (2008) Spatial decision support in the pedagogical area: processing travel stories to discover itineraries hidden beneath the surface. In: The European information society – taking geoinformation science one step further, Proceedings of the 11th Agile International Conference on Geographic Information Science (AGILE 2008), LNCG, pp 359–378

    Google Scholar 

  • Mark D., Comas D., Egenhofer M., Freudschuh S., Gould M., Nunes J. (1995) Evaluating and refining computational models of spatial relations through cross-linguistic human-subjects testing. In: Frank A. U., Kuhn W. (eds) Spatial information theory, a theoretical basis for GIS, LNCS 988. International Conference COSIT’95. Springer, Berlin

    Google Scholar 

  • McKinsey J., Tarski A. (1944) The algebra of topology. Annals of mathematics 45:141–191

    Google Scholar 

  • Miron A. D., Gensel J., Villanova-Oliver M., Martin H. (2007) Relations spatiales qualitatives dans les ontologies géographiques avec ONTOAST. In: SAGEO 2007, Rencontres internationales Géomatique et territoire

    Google Scholar 

  • Montserrat-Adell J, Sánchez M., Ruiz F. J., Agell N. (2016) From qualitative absolute order-of-magnitude to the extended set of hesitant fuzzy linguistic term sets. In: 29th International Workshop on Qualitative Reasoning (QR), IJCAI 2016, New York, USA

    Google Scholar 

  • Moore R. (1966) Interval analysis. Englewood Cliffs, New Jersey

    Google Scholar 

  • Mossakowski T., Schröder L., Wölfl, S. (2006) A categorical perspective on qualitative constraint calculi. In: Qualitative constraint calculi: application and integration, workshop at KI 2006, proceedings, pp 28–39

    Google Scholar 

  • Muller P. (1998) Éléments d’une théorie du mouvement pour la formalisation du raisonnement spatio-temporel de sens commun. PhD thesis, IRIT, Université Paul Sabatier, Toulouse, France

    Google Scholar 

  • Muscettola N., Nayak P., Pell B., Williams B. (1998) Remote agent: to boldly go where no AI system has gone before. Artif Intell 103(1–2):5–47

    Google Scholar 

  • Napoli A., Le Ber F. (2007) The Galois lattice as a hierarchical structure for topological relations. Ann. Math. Artif. Intell. 49(1–4):171–190

    Google Scholar 

  • Ndiaye A., Della Valle G., Roussel P. (2009) Qualitative modelling of a multi-step process: the case of French breadmaking. Expert Syst. Appl. 36(2):1020–1038

    Google Scholar 

  • Nebel B. (1996) Solving hard qualitative temporal reasoning problems: evaluating the efficiency of using the ORD-Horn class. In: Proceeding of the twelfth European Conference on Artificial Intelligence (ECAI’96)

    Google Scholar 

  • Nebel B., Bürckert H.-J. (1995) Reasoning about temporal relations: a maximal tractable subclass of Allen’s interval algebra. J ACM 42(1):43–66

    Google Scholar 

  • Osmani A. (1999) Introduction to reasoning about cyclic intervals. In: Imam I., Kodratoff Y., El-Dessouki A., Ali M. (eds) Multiple approaches to intelligent systems, Proceedings of IEA/AIE-99. Springer LNCS, vol 1611, pp 698–706

    Google Scholar 

  • Osmani A., Lévy F. (2000) A constraint-based approach to simulate faults in telecommunication networks. In: Loganantharaj R., Palm G. (eds) IEA/AIE. Lecture notes in computer science, vol 1821. Springer, Berlin, pp 463–473

    Google Scholar 

  • Picardi C., Bray R., Cascio F., Console L., Dague P., Dressler O., Millet D., Rehfus B., Struss P., Vallée C. (2002) IDD: integrating diagnosis in the design of automotive systems. In: Proceedings of the European Conference on Artificial Intelligence, pp 628–632

    Google Scholar 

  • Poupeau B., Bonin O. (2006) 3D Analysis with high-level primitives: a crystallographic approach. In: Progress in spatial data handling, proceedings of SDH’06. Springer, Berlin, pp 599–616

    Google Scholar 

  • Prior A. (1957) Time and Modality. Clarendon, Oxford

    Google Scholar 

  • Prior A. (1967) Past. Oxford University, Oxford, Present and Future

    Google Scholar 

  • Przytula-Machrouh E., Ligozat G., Denis M. (2004) Vers des ontologies transmodales pour la description d’itinéraires: Le concept de scène élémentaire. Revue Internationale de Géomatique

    Google Scholar 

  • Pujari A. K, Kumari G. V, Sattar A. (1999) INDU: an interval and duration network. In: Australian joint conference on Artificial Intelligence, pp 291–303

    Google Scholar 

  • Raiman O. (1991) Order of magnitude reasoning. Artif. Intell. 51(1–3):11–38

    Google Scholar 

  • Randell D., Cui Z., Cohn T. (1992a) An interval logic for space based on connection. In: Neumann B. (ed) Proceedings of ECAI-92. Wiley, New Jersey, pp 394–398

    Google Scholar 

  • Randell D., Cui Z., Cohn T. (1992b) A spatial logic based on regions and connection. In: Neumann B. (ed) Proceedings of KR-92, CA. Morgan Kaufmann, San Mateo, pp 165–176

    Google Scholar 

  • Renz J. (1999) Maximal tractable fragments of the region connection calculus: a complete analysis. In: Dean T. (ed) IJCAI. Morgan Kaufmann, USA, pp 448–455

    Google Scholar 

  • Renz J., Nebel B. (2007) Qualitative spatial reasoning using constraint calculi. In [Aiello et al. 2007a], pp 161–215

    Google Scholar 

  • Roselló L., Prats F., Agell N., Sánchez M. (2010) Measuring consensus in group decisions by means of qualitative reasoning. Int J Approx Reason 51(4):441–452

    Google Scholar 

  • Ross N., Bradley E., Hertzberg J. (2006) Dynamics-informed data assimilation in a qualitative fluids model. In: Proceedings of the 20th International Workshop on Qualitative Reasoning

    Google Scholar 

  • Sioutis M., Condotta J.-F., Salhi Y., Mazure B. (2015a) Generalized qualitative spatio-temporal reasoning: complexity and tableau method. In: Proceedings of the 24th International Conference automated reasoning with analytic tableaux and related methods (TABLEAUX’15), pp 54–69

    Google Scholar 

  • Sioutis M., Li S., Condotta J.-F. (2015b) Efficiently characterizing non-redundant constraints in large real world qualitative spatial networks. In: Proceedings of the twenty-fourth International Joint Conference on Artificial Intelligence (IJCAI’15), pp 3229–3235

    Google Scholar 

  • Stell J. (2000) Boolean connection algebras: a new approach to the region-connection calculus. Artif. Intell. 122:111–136

    Google Scholar 

  • Struss P. (2002) Automated abstraction of numerical simulation models-theory and practical experience. In: Proceedings of the sixteenth International Workshop on Qualitative Reasoning, Sitges, Catalonia, Spain

    Google Scholar 

  • Struss P., Price C. (2003) Model-based systems in the automotive industry. AI Mag 24(4):17

    Google Scholar 

  • Struss P., Sterling R., Febres J., Sabir U., Keane M. M. (2014) Combining engineering and qualitative models to fault diagnosis in air handling units. In: Proceedings of the twenty-first European Conference on Artificial Intelligence. IOS, Amsterdam, pp 1185–1190

    Google Scholar 

  • Tarski A. (1941) On the calculus of relations. J. Symb. Log 6(3):73–89

    Google Scholar 

  • Top J., Akkermans H.(1991) Computational and physical causality. In: Proceedings of the international joint conference of Artificial Intelligence, pp 1171–1176

    Google Scholar 

  • Travé L., Dormoy J. (1988) Qualitative calculus and applications. In: IMACS transactions on scientific computing’88, pp 53–61

    Google Scholar 

  • Travé L., Kaszkurewicz E. (1986) Qualitative controllability and observability of linear dynamical systems. Proceedings of the IFAC/IFORS Symposium on Large Scale Systems: Theory and Applications 2:964–970

    Google Scholar 

  • Travé-Massuyés L., Dague P. (2003) Modèles et raisonnements qualitatifs. Hermès

    Google Scholar 

  • Travé-Massuyès L., Dormoy J. (1990) Numéro Spécial sur le Raisonnement Qualitatif. Revue d’Intelligence Artificielle 3/4

    Google Scholar 

  • Travé-Massuyès L., Dormoy J., Guerrin F. (1997) Le raisonnement qualitatif pour les sciences de l’ingénieur (coll. Hermès, Diagnostic et Maintenance)

    Google Scholar 

  • Travé-Massuyès L., Ironi L., Dague P. (2003) Mathematical foundations of qualitative reasoning. AI Mag 24(4):91

    Google Scholar 

  • Travé-Massuyès L., Milne R. (1997) Gas-turbine condition monitoring using qualitative model-based diagnosis. IEEE Expert Intell Syst Appl 12(3):22–31

    Google Scholar 

  • Travé-Massuyès L., Milne R. (2009) Application oriented qualitative reasoning. The Knowledge Engineering Review 10(02):181–204

    Google Scholar 

  • Travé-Massuyès L., Piera N. (1989) The orders of magnitude models as qualitative algebras. In: Proceedings of the 11th International Joint Conference on Artificial Intelligence -vol 2. Morgan Kaufmann, USA, pp 1261–1266

    Google Scholar 

  • Travé-Massuyès L, Prats F, Sánchez M., Agell N. (2005) Relative and absolute order-of-magnitude models unified. Ann Math Artif. Intell. 45(3):323–341

    Google Scholar 

  • van Beek P. (1990) Reasoning about qualitative temporal information. In: Proceedings of AAAI-90, Boston, MA, pp 728–734

    Google Scholar 

  • van Beek P., Manchak D. W. (1996) The design and experimental analysis of algorithms for temporal reasoning. J. Artif. Intell. Res 4:1–18

    Google Scholar 

  • van de Weghe N. (2004) Representing and reasoning about moving objects: a qualitative approach. PhD thesis, Ghent University

    Google Scholar 

  • Vieu L. (1991) Sémantique des relations spatiales et inférences spatio-temporelles: Une contribution à l’étude des structures formelles de l’espace en Langage Naturel. PhD thesis, Université Paul Sabatier, Toulouse, France

    Google Scholar 

  • Vilain M., Kautz H. A., van Beek P. G. (1989) Constraint propagation algorithms for temporal reasoning: a revised report. In: Weld D, de Kleer J (eds) Readings in qualitative reasoning about physical systems. Morgan Kaufmann, USA

    Google Scholar 

  • Vilain M. B. (1982) A system for reasoning about time. In: Proceedings of AAAI-82, pp 197–201

    Google Scholar 

  • Wallgrün J. O., Frommberger L., Wolter D., Dylla F., Freksa C. (2006a). Qualitative spatial representation and reasoning in the sparQ-toolbox. In [Barkowsky et al. 2008], pp 39–58

    Google Scholar 

  • Wallgrün J. O., Frommberger L., Wolter D., Dylla F., Freksa C. (2006b) Qualitative spatial representation and reasoning in the SparQ-toolbox. In [Barkowsky et al. 2008], pp 39–58

    Google Scholar 

  • Weld D., de Kleer J. E. (1989) Readings in qualitative reasoning about physical systems. Morgan Kaufmann, San Francisco

    Google Scholar 

  • Westphal M. (2014) Qualitative Constraint-based Reasoning: methods and applications. PhD thesis, Universitt Freiburg

    Google Scholar 

  • Westphal M., Hué J., Wölfl S. (2014) On the scope of qualitative constraint calculi. KI 2014 Advances in Artificial Intelligence. Springer, Berlin, pp 207–218

    Google Scholar 

  • Westphal M., Wöfl S. (2008) Bipath consistency revisited. In: Proceedings of the ECAI workshop on Spatial and Temporal Reasoning

    Google Scholar 

  • Westphal M., Wölfl S .(2009) Qualitative CSP, finite CSP, and SAT: comparing methods for qualitative constraint-based reasoning. In [Boutilier 2009], pp 628–633

    Google Scholar 

  • Williams B., Nayak P. (1996) A model-based approach to reactive self-configuring systems. In: Proceedings of the National Conference on Artificial Intelligence, pp 971–978

    Google Scholar 

  • Wolter F., Zakharyaschev M. (2000) Spatio-temporal representation and reasoning based on RCC-8. In: Proceedings of the Seventh International Conference KR 2000. Morgan Kaufmann, USA, pp 3–14

    Google Scholar 

  • Würbel E., Jeansoulin R., Papini O. (2000) Revision: an application in the framework of GIS. KR 2000:505–515

    Google Scholar 

  • Yang Y., Atif J., Bloch I. (2015) Abductive reasoning using tableau methods for high-level image interpretation. 38th Annual German conference on AI. Dresden, Germany, pp 356–365

    Google Scholar 

  • Yilmaz O., Say A. (2006) Causes of ineradicable spurious predictions in qualitative simulation. J. Artif. Intell. Res. 27:551–575

    Google Scholar 

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Authors and Affiliations

  1. CRIL-CNRS and Université d’Artois, Lens, France

    Jean-François Condotta

  2. ICube, Université de Strasbourg, ENGEES, CNRS, Strasbourg, France

    Florence Le Ber

  3. LIMSI-CNRS, Orsay, France

    Gérard Ligozat

  4. LAAS-CNRS, Toulouse, France

    Louise Travé-Massuyès

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  1. Jean-François Condotta
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  2. Florence Le Ber
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  3. Gérard Ligozat
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  4. Louise Travé-Massuyès
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Correspondence to Jean-François Condotta .

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Editors and Affiliations

  1. CRIL-CNRS, Université d'Artois and Institut Universitaire de France, Lens, France

    Pierre Marquis

  2. Aix Marseille Université, Université de Toulon, CNRS, LIS, Marseille, France

    Odile Papini

  3. IRIT, CNRS and Université Paul Sabatier, Toulouse, France

    Henri Prade

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Condotta, JF., Le Ber, F., Ligozat, G., Travé-Massuyès, L. (2020). Qualitative Reasoning. In: Marquis, P., Papini, O., Prade, H. (eds) A Guided Tour of Artificial Intelligence Research. Springer, Cham. https://doi.org/10.1007/978-3-030-06164-7_5

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