Abstract
Reasoning about actions, change, and causality constitutes an important field of research in artificial intelligence. Several formal action languages have been proposed, addressing the need to qualify change and facilitate (commonsense) reasoning in dynamic settings. The Event Calculus (EC), in particular, permits the representation of causal and narrative information. Although action languages are well established as a means to model dynamic domains, their adoption by knowledge engineers is often hindered by modelling errors and steep learning curves. It has been argued that visual modelling tools could assist knowledge engineers in their modelling tasks and improve the quality of the resulting models by obtaining a better understanding of the semantics. We present ECAVI (Event Calculus Analysis and VIsualisation), a domain-independent visual modelling tool for designing dynamic domains in the Event Calculus. ECAVI is mainly addressed to inexperienced modellers, aiming to acquaint them with the features of the Event Calculus and to guide them during the process of designing their dynamic problem settings.
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References
Brambilla, M., Cabot, J., Wimmer, M.: Model-Driven Software Engineering in Practice: Second Edition, 2nd edn. Morgan & Claypool Publishers (2017)
Choe, Y., Lee, M.: Algebraic method to model secure IoT. In: Domain-Specific Conceptual Modeling, pp. 335–355 (2016). https://doi.org/10.1007/978-3-319-39417-6_15
Dogmus, Z., Erdem, E., Patoglu, V.: ReAct!: An interactive educational tool for AI planning for robotics. IEEE Trans. Educ. 58, 15–24 (2015). https://doi.org/10.1109/te.2014.2318678. https://app.dimensions.ai/details/publication/pub.1061587896
Faber, W., Woltran, S.: Manifold answer-set programs for meta-reasoning. In: Logic Programming and Nonmonotonic Reasoning, LPNMR 2009 (2008). https://doi.org/10.1007/978-3-642-04238-6_12
Ferraris, P., Lee, J., Lifschitz, V.: Stable models and circumscription. Artificial Intelligence 175(1), 236–263 (2011)
Fill, H.-G., Karagiannis, D.: On the conceptualisation of modelling methods using the ADOxx meta modelling platform. Enterp. Modell. Inf. Syst. Archit. 8, 4–25 (2013)
Fowler, M.: UML Distilled: A Brief Guide to the Standard Object Modeling Language, 3rd edn. Addison-Wesley Longman Publishing (2003)
Gebser, M., Kaufmann, B., Neumann, A., Schaub, T.: Clasp: A conflict-driven answer set solver. In: Logic Programming and Nonmonotonic Reasoning, LPNMR 2007 (2007). https://doi.org/10.1007/978-3-540-72200-7_23
Gelfond, M., Lifschitz, V.: The Stable Model Semantics For Logic Programming, pp. 1070–1080. MIT Press (1988)
Karagiannis, D., Mayr, H.C., Mylopoulos, J.: Domain-Specific Conceptual Modeling: Concepts, Methods and Tools, 1st edn. Springer Publishing Company (2016)
Karagiannis, D., Kühn, H.: Metamodelling platforms. In: Proceedings of the Third International Conference on E-Commerce and Web Technologies, EC-WEB ’02, 182 (2002). https://doi.org/10.5555/646162.680499
Kloimüllner, C., Oetsch, J., Pührer, J., Tompits, H.: Kara: A system for visualising and visual editing of interpretations for answer-set programs. In: Applications of Declarative Programming and Knowledge Management, INAP 2011, WLP 2011 (2011). https://doi.org/10.1007/978-3-642-41524-1_20
Kowalski, R., Sergot, M.: A logic-based calculus of events. New Gener. Comput. 4, 67–95 (1986). https://doi.org/10.1007/BF03037383
Lee, J., Palla, R.: Reformulating the situation calculus and the event calculus in the general theory of stable models and in answer set programming. J. Artif. Intell. Res. 43 (2012). https://doi.org/10.5555/2387915.2387930
Levesque, H., Pirri, F., Reiter, R.: Foundations for the situation calculus. Electron. Trans. Artif. Intell. 2, 159–178 (1998). https://ep.liu.se/ej/etai/1998/005/
Lifschitz, V.: What is answer set programming? In: Proceedings of the 23rd National Conference on Artificial Intelligence - Volume 3, pp. 1594–1597 (2008). https://doi.org/10.5555/1620270.1620340
McCarthy, J.: Stanford Artificial Intelligence Laboratory (1963). Situations, Actions, and Causal Laws. Memo (Stanford Artificial Intelligence Project). Comtex Scientific https://books.google.gr/books?id=iF8iGwAACAAJ
Miller, R., Shanahan, M.: Some alternative formulations of the event calculus. Comput. Logic Logic Programm. Beyond, 452–490 (2002). https://doi.org/10.1007/3-540-45632-5_17
Morgan, R., Grossmann, G., Schrefl, M., Stumptner, M., Payne, T.: VizDSL: Towards a graphical visualisation language for enterprise systems interoperability. In: Advanced Information Systems Engineering, CAiSE 2018 (2017). https://doi.org/10.1007/978-3-319-91563-0_27
Mueller, E.: Commonsense Reasoning, 1st edn. Morgan Kaufmann (2006)
Musen, M.A., Protégé, T.: The Protégé Project: A look back and a look forward. In: AI Matters. Association of Computing Machinery Specific Interest Group in Artificial Intelligence, vol. 1(4) (2015). https://doi.org/10.1145/2757001.2757003
Oetsch, J., Pührer, J., Tompits, H.: The SeaLion has landed: An IDE for answer-set programming–preliminary report. In: Applications of Declarative Programming and Knowledge Management, INAP 2011, WLP 2011, pp. 305–324 (2013). https://doi.org/10.1007/978-3-642-41524-1_19
Ribeiro, T., Inoue, K., Bourgne, G.: Combining answer set programs for adaptive and reactive reasoning. Theory Pract. Logic Programm. 13 (2013). https://hal.archives-ouvertes.fr/hal-01562133
Siau, K., Loo, P.-P.: Identifying difficulties in learning UML. IS Management 23, 43–51 (2006). https://doi.org/10.1201/1078.10580530/46108.23.3.20060601/93706.5
Silva, A.R.da.: Model-driven engineering: A survey supported by the unified conceptual model. Comput. Lang. Syst. Struct. 43, 139–155 (2015)
Van Harmelen, F., Lifschitz, V., Porter, B.: Handbook of Knowledge Representation. Elsevier Science (2007)
Van Lambalgen, M., Hamm, F.: The Proper Treatment of Events (2006)
Visic, N., Fill, H.-G., Buchmann, R.A., Karagiannis, D.: A domain-specific language for modeling method definition: From requirements to grammar. In: 2015 IEEE 9th International Conference on Research Challenges in Information Science (RCIS), pp. 286–297 (2015). https://doi.org/10.1109/RCIS.2015.7128889
Yamasaki, S., Sasakura, M.: A calculus effectively performing event formation with visualization. In: High-Performance Computing, ISHPC 2005, ALPS 2006, pp. 287–294 (2008). https://doi.org/10.1007/978-3-540-77704-5_27
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Basina, N., Patkos, T., Plexousakis, D. (2022). ECAVI: An Assistant for Reasoning About Actions and Change with the Event Calculus. In: Karagiannis, D., Lee, M., Hinkelmann, K., Utz, W. (eds) Domain-Specific Conceptual Modeling. Springer, Cham. https://doi.org/10.1007/978-3-030-93547-4_20
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