• JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
 
  Bookmark and Share
 
 
Doctoral Thesis
DOI
10.11606/T.3.2011.tde-11042011-074633
Document
Author
Full name
Tiago Stegun Vaquero
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2011
Supervisor
Committee
Silva, José Reinaldo (President)
Barros, Leliane Nunes de
Beck, John Christopher
Cozman, Fabio Gagliardi
Maruyama, Newton
Title in Portuguese
Análise de pós-design para aplicações de planejamento em IA.
Keywords in Portuguese
Design
Inteligência Artificial (planejamento)
Mecatrônica
Representação de conhecimento
Abstract in Portuguese
Desde o final da década de 1990 existe um interesse crescente na aplicação de técnicas de planejamento automático em IA para resolver problemas reais de engenharia. Além das características dos problemas acadêmicos, tais como a necessidade de raciocinar sobre as ações, problemas reais requerem elicitação, engenharia e gerenciamento detalhado do conhecimento do domínio. Para tais aplicações reais, um processo de design sistemático é necessário onde as ferramentas de Engenharia do Conhecimento e de Requisitons têm um papel fundamental. Esforços acadêmicos recentes na área da Engenharia do Conhecimento em planejamento automático vêm desenvolvido ferramentas e técnicas de apoio ao processo de design de modelos do conhecimento. Porém, dada a natural incompletude do conhecimento, experiência prática em aplicações reais, como por exemplo exploração do espaço, tem mostrado que, mesmo com um processo disciplinado de design, requisitos de pontos de vista diferente (por exemplo, especialistas, usuários e patrocinadores) ainda surgem após a análise, geração e execução de planos. A tese central deste texto é que uma fase de análise de pós-design para o desenvolvimento de aplicações de planejamento em IA resulta em modelos do conhecimento mais ricos e, conseqüentemente, aumenta a qualidade dos planos gerados e a performance dos planejadores automáticos. Neste texto, nós investigamos como os conhecimentos e requisitos ocultos podem ser adquiridos e reutilizados durante a fase de análise de plans (posterior ao design do modelo) e como estes conhecimentos afetam o desempenho do processo de planejamento automático. O texto descreve um framework de post-design chamado postDAM que combina (1) uma ferramenta de engenharia de conhecimento para a aquisição de requisitos e avaliação do plano, (2) um ambiente de prototipagem virtual para a análise e simulação de planos, (3) um sistema de banco de dados para armazenamento de avaliações de planos, e (4) um sistema de raciocínio ontológico para o re-uso e descoberta de conhecimento sobre o domínio. Com o framework postDAM demonstramos que a análise de pós-design auxilia a descoberta de requisitos ocultos e orienta o ciclo de refinamento do modelo. Este trabalho apresenta três estudos de caso com domínios conhecidos na literatura e oito planejadores do estado da arte. Nossos resultados demonstram que melhorias significativas na qualidade do plano e um aumento na velocidade dos planejadores de até três ordens de grandeza pode ser alcançada através de um processo disciplinado e cuidados de pós-design. Nós demonstramos também que rationales provenientes dos usuários capturados durante as avaliações de planos podem ser úteis e reutilizáveis em novas avaliações de plano e em novos projetos. Nós argumentamos que esse processo de pós-design é fundamental para a implantação da tecnologia de planejamento automático em aplicações do mundo real. Até onde sabemos, este é o primeiro trabalho que investiga a análise de pós-design em aplicações de planejamento automático da IA.
Title in English
Post-design analysis for AI planning applications.
Keywords in English
Artificial Intelligence (planning)
Design
Knowledge representation
Mechatronics
Abstract in English
Since the end of the 1990s there has been an increasing interest in the application of AI planning techniques to solve real-life problems. In addition to characteristics of academic problems, such as the need to reason about actions, real-life problems require detailed knowledge elicitation, engineering, and management. A systematic design process in which Knowledge and Requirements Engineering techniques and tools play a fundamental role is necessary in such applications. Research on Knowledge Engineering for planning and scheduling has created tools and techniques to support the design process of planning domain models. However, given the natural incompleteness of the knowledge, practical experience in real applications such as space exploration has shown that, even with a disciplined process of design, requirements from different viewpoints (e.g. stakeholders, experts, users) still emerge after plan generation, analysis and execution. The central thesis of this dissertation is that an post-design analysis phase in the development of AI planning applications leads to richer knowledge models and, consequently, to high-performance and high-quality plans. In this dissertation, we investigate how hidden knowledge and requirements can be acquired and re-used during a plan analysis phase that follows model design and how they affect planning performance. We describe a post-design framework called postDAM that combines (1) a knowledge engineering tool for requirements acquisition and plan evaluation, (2) a virtual prototyping environment for the analysis and simulation of plans, (3) a database system for storing plan evaluations, and (4) an ontological reasoning system for knowledge re-use and discovery. Our framework demonstrates that post-design analysis supports the discovery of missing requirements and guides the model refinement cycle. We present three case studies using benchmark domains and eight state-of-the-art planners. Our results demonstrate that significant improvements in plan quality and an increase in planning speed of up to three orders of magnitude can be achieved through a careful post-design process. We also demonstrate that rationales captured during plan evaluations from users can be useful and reusable in further plan evaluations and in new application designs. We argue that such a post-design process is critical for deployment of planning technology in real-world applications. To our knowledge, this is the first work that investigate post-design analysis for AI planning applications.
 
WARNING - Viewing this document is conditioned on your acceptance of the following terms of use:
This document is only for private use for research and teaching activities. Reproduction for commercial use is forbidden. This rights cover the whole data about this document as well as its contents. Any uses or copies of this document in whole or in part must include the author's name.
Publishing Date
2011-04-19
 
WARNING: The material described below relates to works resulting from this thesis or dissertation. The contents of these works are the author's responsibility.
  • SILVA, J. R., et al. itSIMPLE: towards an integrated design system for real planning applications [doi:10.1017/s0269888912000434]. Knowledge Engineering Review [online], 2013, vol. 28, p. 1-16.
  • VAQUERO, Tiago Stegun, José Reinaldo Siliva, and Beck, J.C. Post-design analysis for building and refining AI planning systems. Engineering Applications of Artificial Intelligence [online], 2013, vol. 26, p. 1967-1979. Available from: http://ww.sciencedirect.com/science/article/pii/S0952197613000729.
  • VAQUERO, Tiago Stegun, et al. Knowledge Engineering for Planning and Scheduling: Tools and Methods. The Journal of Artificial Intelligence Research , 2013.
  • ROMERO, V.M.C., et al. Analysis and Management of Plans provided by Automated Planning Systems. In VIII SBAI - Simpósio Brasileiro de Automação Inteligente, Florianopolis, 2007. Procc. of VIII SBAI - Simpósio Brasileiro de Automação Inteligente., 2007.
  • TAVARES, J. J. P. Z. S., et al. Integração de Planejamento Automático em Sistemas Reais Baseados em CLPs. In Simpósio Brasileiro de Automação Inteligente, São João del Rei, 2011. Proceedings do X SBAI., 2011. Dispon?vel em: http://www.sbai2011.ufsj.edu.br/.
  • Tonaco, R., VAQUERO, Tiago Stegun, and SILVA, J. R. Requirements Analysis Method for Real World Systems in Automated Planning. In Int. Conference in Automated Planning and Scheduling, Roma, 2013. Procc. of ICAPS 2013., 2013. Available from: http://icaps13.icaps-conference.org.
  • VAQUERO, Tiago Stegun, et al. An Integrated Tool for Designing Planning Domains. In International Conference on Automated Planning & Scheduling (ICAPS 2007), Providence, 2007. Procc. of International Conference on Automated Planning & Scheduling (ICAPS 2007., 2007. Available from: http://abotea.rsise.anu.edu.au/icaps07/index.php?page=accepted-papers.
  • VAQUERO, Tiago Stegun, et al. itSfIMPLE 4.0: Enhancing the Modeling Experience of Planning Problems. In ICAPS - Int. Conf. on Artificial Planning and Scheduling, Atibaia, 2012. Annals of ICAPS 2012.New York : AAAI Editor, 2012.
  • VAQUERO, Tiago Stegun, et al. itSIMPLE2.0 : An Integrated Tool for Designing Planning Domains. In ICKEPS 2005 Competition on Knowledge Engineering for Planning and Scheduling, Providence, 2007. Proc. of ICKEPS 2005 Competition on Knowledge Engineering for Planning and Scheduling., 2007.
  • VAQUERO, Tiago Stegun, et al. Modeling a Real Application as a Planning Problem by using UML.P. In VIII SBAI - Simpósio Brasileiro de Automação Inteligen, Florianopolis, 2007. Procc. of VIII SBAI - Simpósio Brasileiro de Automação Inteligen., 2007.
  • VAQUERO, Tiago Stegun, et al. Planning and Scheduling Ship Operations on Petroleum Ports and Platforms. In ICAPS - Int. Conf. on Artificial Planning and Scheduling, Atibaia, SP, 2012. Annals of ICAPS 2012.New York : AAAI Editor, 2012.
  • VAQUERO, Tiago Stegun, SILVA, J. R., and Beck, J.C. A Brief Review of Tools and Methods for Knowledge Engineering for Planning & Scheduling. In Int. Conference in Automated Planning and Scheduling, Freiburg, Germay, 2011. Procedings of ICAPS 2011.Menlo Park : AAAI Press, 2011. Available from: http://www.aaai.org/Press/Proceedings/icaps11.php.
  • VAQUERO, Tiago Stegun, SILVA, J. R., and Beck, J.C. A Conceptual Framework for Post.Design Analysis in AI Planning Applications. In Int. Conference in Automated Planning and Scheduling, Freiburg, 2011. Procedings of ICAPS 2011.Menlo Park : AAAI Press, 2011. Available from: http://www.aaai.org/Press/Proceedings/icaps11.php.
  • VAQUERO, Tiago Stegun, SILVA, J. R., and Beck, J.C. Acquisition and Re.use of Plan Evaluation Rationales on Post Design. In Int. Conference in Automated Planning and Scheduling, Freiburg, Germay, 2011. Procedings of ICAPS 2011.Menlo Park : AAAI Press, 2011. Available from: http://www.aaai.org/Press/Proceedings/icaps11.php.
All rights of the thesis/dissertation are from the authors
Centro de Informática de São Carlos
Digital Library of Theses and Dissertations of USP. Copyright © 2001-2023. All rights reserved.