Domain Knowledge and the Design Process

McDermott, John

doi:10.1109/dac.1981.1585413

Cited by 16 publications

(3 citation statements)

References 5 publications

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“…Any planning system is embedded in a real environment, that is, a myriad of ‘non-system’ tools, objects, people, and processes with which it must interact. It is necessary to have a detailed model of this domain environment and it is important that this model be developed independently of the planning system (McDermott, 1981). In itSIMPLE, the modeling phase is composed of dual layered sections: one concerned with the modeling of the environment where the plan is to be executed and the other dealing with a specific planning instance to be solved.…”

Section: The Itsimple Design Environmentmentioning

confidence: 99%

itSIMPLE: towards an integrated design system for real planning applications

Vaquero

Silva

Tonidandel

et al. 2013

The Knowledge Engineering Review

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Since the end of the 1990s, there has been an increasing interest in the application of artificial intelligence (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 tools play a fundamental role is necessary in such applications. One of the main challenges in such design process, and consequently in the study of Knowledge Engineering in AI planning, has been the analysis of requirements and their subsequent transformation into an input-ready model for planners. itSIMPLE is a research project dedicated to the study of a project process to support the design phases of real-life planning models. In this paper, we give an overview of itSIMPLE focusing on the main translation processes among a minimal set of representations: from requirements represented in Unified Modeling Language (UML) to Petri Nets and from UML models to planning domain definition language for problem solving.

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Section: The Itsimple Design Environmentmentioning

confidence: 99%

itSIMPLE: towards an integrated design system for real planning applications

Vaquero

Silva

Tonidandel

et al. 2013

The Knowledge Engineering Review

View full text Add to dashboard Cite

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“…These studies represent the beginning of diversification in research agendas in the area of design thinking. Some of these studies deal with the internal and external representations of designed objects (Gobert, 1989; Akin, 1978), others with the issues of design generation (Cuomo, 1989;McDermott, 1982;Darke, 1979), others with the knowledge base of design thinking (Waldron, elaL, 1989;Akin, 1986), others with the formulation of design problems (Akin, 1991; Caroll, etal, 1978), others with the thought processes that apply to learning (SchOn, 1983;Goor, 1974) and yet others with refining the general descriptions of the design process offered by the Initial group of studies (Chan, 1990;Eckersley, 1988). In parallel and quite unrelated to these studies researchers and scholars have also dealt with prescriptive accounts of the design process.…”

Section: Studies Of Design Thinkingmentioning

confidence: 99%

Architects' reasoning with structures and functions

Akın

1993

Environ. Plann. B

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While there is a visible increase of publications in the area of design thinking and signs that it is becoming a serious area of research, there is a lack of theoretical approaches that directly address its domain specific characteristics. This study attempts to develop such a theory directed towards design reasoning based on a protocol study and formal notation, among other things. Three domains of reasoning are described: construction, object, and representation. Inference making within and between these domains is described in terms of operations called functions and states called structures in a state-space representation of design. Five types of mapping which are illustrated by the protocol study are described using structures and functions. Both shortcomings and strengths of the proposed theoretical formalisms are discussed. Future work is indicated. Studies of Design ThinkingDescriptive studies of architectural design are relatively recent. Inspired by studies in management science, cognitive psychology and computer science, 1 Eastman conducted the first known protocol study of architectural design (1969, 1970). This was followed by a number of studies, both at Carnegie Mellon and elsewhere which resembled the initial work by Eastman in some sense: methodologically, substantively or both. 3 These studies of the design process were concerned with characterizing the process in its most general form, identifying the operations and representations which were responsible for the development of designs, calibrating the operational aspects of the human cognitive system, describing design tasks in the context of a general taxonomy of taska, and doing all of this within the paradigms of information processing theory originally developed for the study of human problem solving (Newell etal., 1972). The results of these works indicate that, 1) the design process exhibits characteristics that are shared by other information processing phenomenon, 2) certain behaviors of designers can be basically described using various cognitive and problem solving models, and 3) some aspects of design behavior go beyond those that can be demonstrated by simple, algorithmic procedures.Subsequently, researchers seasoned by this initial encounter with the often overwhelming scope of issues subsumed under the general heading of design as well as others entering the field from related areas of design, especially form engineering design, built upon this early foundation. These studies represent the beginning of diversification in research agendas in the area of design thinking. Some of these studies deal with the internal and external representations of designed objects (Gobert, 1989; Akin, 1978), others with the issues of design generation (Cuomo, 1989;McDermott, 1982;Darke, 1979), others with the knowledge base of design thinking (Waldron, elaL, 1989;Akin, 1986), others with the formulation of design problems (Akin, 1991; Caroll, etal, 1978), others with the thought processes that apply to learning (SchOn, 1983;Goor, 1974)...

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“…Any planning system is embedded in a real domain: a myriad of "non-system" tools, objects, people, and processes with which it must interact. It is necessary to have a model for this environment -and it is important that this model be developed independently of the planning system (MCDERMOTT, 1981). The term model implies that we have a representation or a formalism that mirrors behaviors in the real domain.…”

Section: Knowledge Modelingmentioning

confidence: 99%

Análise de pós-design para aplicações de planejamento em IA.

Vaquero¹

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AcknowledgementsFirst and above all, I praise God, the almighty for providing me this opportunity and granting me the capability to proceed successfully. This thesis appears in its current form due to the guidance and contribution, both directly and indirectly, of several people. I would therefore like to offer my sincere thanks to all of them.I would firstly like to thank my supervisors, Professor José Reinaldo Silva and Professor J. Christopher Beck, for being great advisors and role models, for all of your suggestions and ideas, and for taking the time to explain and discuss all aspects of research to me.Thanks to all my colleagues in the following labs: Design Lab at the University of São Paulo, TIDEL at the University of Toronto, and IAAA at the University Center of FEI -you have all helped me at some point.Thanks to my parents, Gilberto and Sônia, for years of support and love.Last and most, thanks to my lovely sweet wife Patrícia for all her love and support, and for her great patience and understandings. AbstractSince 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 ...

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Domain Knowledge and the Design Process

Cited by 16 publications

References 5 publications

itSIMPLE: towards an integrated design system for real planning applications

itSIMPLE: towards an integrated design system for real planning applications

Architects' reasoning with structures and functions

Análise de pós-design para aplicações de planejamento em IA.

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