Ciência da Computação
URI permanente desta comunidadehttps://repositorio.fei.edu.br/handle/FEI/342
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Resultados da Pesquisa
Artigo de evento 11 Citação(ões) na Scopus On the use of UML.P for modeling a real application as a planning problem(2006) VAQUERO, T. S.; Flavio Tonidandel; BARROS, L. N. DE; SILVA, J. R.There is a great interest in the planning community to apply all developments already achieved in the area to real applications. Such scenario makes the community focus on Knowledge Engineering (KE) applied in modeling of planning problems and domains. In this paper, we propose the use of UML for Planning Approach, denominated UML.P, during planning domain modeling process. We also discuss the exposure of UML.P to a real application, e.g., the sequencing car problems in an assembly line. This modeling experience, using a classical manufacturing problem, provides some insights and considerations that can contribute to a general KE process for planning. Copyright © 2006, American Association for Artificial Intelligence (www.aaai.org). All rights reserved.Artigo de evento 38 Citação(ões) na Scopus itSIMPLE2.0: An integrated tool for designing planning domains(2007-09-26) VAQUERO, T. S.; ROMERO, V.; Flavio Tonidandel; SILVA, J. R.A great effort has been made today in the area of Artificial Intelligence for defining reliable automated planning systems that can be applied in real life applications. That leads to the need of a systematic design process, in which the initial phases are not neglected and where Knowledge and Requirement Engineering tools have a fundamental role for supporting designers. Following this principle, this paper presents the evolution of the tool itSIMPLE which implements a KE integrated environment where designers can perform knowledge acquisition, domain modeling, domain model analysis, model testing, maintenance and plan analysis processes by using different well-known languages such as UML, Petri Nets, PDDL and XML, each one of them with its best contribution. The tool supports users in an organized object-oriented domain design process with a friendly and easy-to-use interface. Copyright © 2007, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.- Reading PDDL, writing an object-oriented model(2006-10-27) Flavio Tonidandel; VAQUERO, T. S.; SILVA, J. R.There are many efforts towards a combination of planning systems and real world applications. Although the PDDL is in constant evolution, which improves its capability to describe real domains, it is still a declarative language that is not so simple to be used by the non-planning community. This paper describes a translation process that reads a domain specification in PDDL and transforms it into an object-oriented model, more specifically into a version of UML for planning approaches. This translation process can let a designer read PDDL domains and verify it with some powerful tool like itSIMPLE or GIPO, or it can allow a planning system that only reads object-oriented models to run in domains described in PDDL originally. © Springer-Verlag Berlin Heidelberg 2006.
- Formal knowledge engineering for planning: Pre and post-design analysis(2020-03-25) SILVA, J. R.; SILVA, J. M. Javier Martinez Silva; VAQUERO, T. S.© Springer Nature Switzerland AG 2020.The interest and scope of the area of autonomous systems have been steadily growing in the last 20 years. Artificial intelligence planning and scheduling is a promising technology for enabling intelligent behavior in complex autonomous systems. To use planning technology, however, one has to create a knowledge base from which the input to the planner will be derived. This process requires advanced knowledge engineering tools, dedicated to the acquisition and formulation of the knowledge base, and its respective integration with planning algorithms that reason about the world to plan intelligently. In this chapter, we shortly review the existing knowledge engineering tools and methods that support the design of the problem and domain knowledge for AI planning and scheduling applications (AI P&S). We examine the state-of-the-art tools and methods of knowledge engineering for planning & scheduling (KEPS) in the context of an abstract design process for acquiring, formulating, and analyzing domain knowledge. Planning quality is associated with requirements knowledge (pre-design) which should match properties of plans (post-design). While examining the literature, we analyze the design phases that have not received much attention, and propose new approaches to that, based on theoretical analysis and also in practical experience in the implementation of the system itSIMPLE.