Author(s):  
Norasyikin Omar ◽  
◽  
Mimi Mohaffyza Mohamad ◽  
Marina Ibrahim Mukhtar ◽  
Aini Nazura Paimin ◽  
...  

2009 ◽  
pp. 950-960
Author(s):  
Kazuhisa Seta

In ontological engineering research field, the concept of “task ontology” is well-known as a useful technology to systemize and accumulate the knowledge to perform problem-solving tasks (e.g., diagnosis, design, scheduling, and so on). A task ontology refers to a system of a vocabulary/ concepts used as building blocks to perform a problem-solving task in a machine readable manner, so that the system and humans can collaboratively solve a problem based on it. The concept of task ontology was proposed by Mizoguchi (Mizoguchi, Tijerino, & Ikeda, 1992, 1995) and its validity is substantiated by development of many practical knowledge-based systems (Hori & Yoshida, 1998; Ikeda, Seta, & Mizoguchi, 1997; Izumi &Yamaguchi, 2002; Schreiber et al., 2000; Seta, Ikeda, Kakusho, & Mizoguchi, 1997). He stated: …task ontology characterizes the computational architecture of a knowledge-based system which performs a task. The idea of task ontology which serves as a system of the vocabulary/concepts used as building blocks for knowledge-based systems might provide an effective methodology and vocabulary for both analyzing and synthesizing knowledge-based systems. It is useful for describing inherent problem-solving structure of the existing tasks domain-independently. It is obtained by analyzing task structures of real world problem. ... The ultimate goal of task ontology research is to provide a theory of all the vocabulary/concepts necessary for building a model of human problem solving processes. (Mizoguchi, 2003) We can also recognize task ontology as a static user model (Seta et al., 1997), which captures the meaning of problem-solving processes, that is, the input/output relation of each activity in a problem-solving task and its effects on the real world as well as on the humans’ mind.


Author(s):  
Kazuhisa Seta

In ontological engineering research field, the concept of “task ontology” is well-known as a useful technology to systemize and accumulate the knowledge to perform problem-solving tasks (e.g., diagnosis, design, scheduling, and so on). A task ontology refers to a system of a vocabulary/concepts used as building blocks to perform a problem-solving task in a machine readable manner, so that the system and humans can collaboratively solve a problem based on it. The concept of task ontology was proposed by Mizoguchi (Mizoguchi, Tijerino, & Ikeda, 1992, 1995) and its validity is substantiated by development of many practical knowledge-based systems (Hori & Yoshida, 1998; Ikeda, Seta, & Mizoguchi, 1997; Izumi &Yamaguchi, 2002; Schreiber et al., 2000; Seta, Ikeda, Kakusho, & Mizoguchi, 1997). He stated: …task ontology characterizes the computational architecture of a knowledge-based system which performs a task. The idea of task ontology which serves as a system of the vocabulary/concepts used as building blocks for knowledge-based systems might provide an effective methodology and vocabulary for both analyzing and synthesizing knowledge-based systems. It is useful for describing inherent problem-solving structure of the existing tasks domain-independently. It is obtained by analyzing task structures of real world problem. ... The ultimate goal of task ontology research is to provide a theory of all the vocabulary/concepts necessary for building a model of human problem solving processes. (Mizoguchi, 2003) We can also recognize task ontology as a static user model (Seta et al., 1997), which captures the meaning of problem-solving processes, that is, the input/output relation of each activity in a problem-solving task and its effects on the real world as well as on the humans’ mind.


Author(s):  
Mohamed E. M. El-Sayed ◽  
Jacqueline A. J. El-Sayed

Problem solving is one of the main activities in achieving design and research goal. While problem solving in general is an activity aiming at transforming unacceptable state of reality to acceptable state of reality, problem solving in engineering is usually a means for tackling other activities such as design and research. By breaking down design and research into a set of engineering problem solving activities, the goals of complicated design and research projects can be achieved. For this reason, the transitions from design or research to problem solving in some cases are unidentifiable. The identification of the problem solving activity goals and the transition between the three activities, however, are essentials for creativity and achieving the desired objectives especially when dealing with conflicting objectives and constraints. In this paper, design, research, and problem solving are distinguished as realization activities performed in different reality domains with different beginning and ending states. These three activities use modeling and simulation as basic elements of mapping between realities to perform analysis and integration. While analysis and simulation are mainly the analytical actions, modeling and integration are mainly the creative actions. With these distinctions, the identification of problem solving activity goals, and transitions between activities, can be easily realized. Also, creativity and dealing with conflicting objectives can be greatly facilitated. To demonstrate these concepts and their implications some illustrative examples are discussed.


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