An Integrated Knowledge-Based Problem Solving System for Structural Optimization

1988 ◽  
pp. 289-297
Author(s):  
K. Schittkowski
Keyword(s):  
Problem Solving ◽  
Structural Optimization ◽  
Knowledge Based ◽  
Integrated Knowledge

An integrated knowledge-based and procedural system for the design of energy conscious buildings

1992 ◽  
Vol 1 (2) ◽  
pp. 123-141 ◽  
Author(s):  
Edna Shaviv ◽  
Yehuda E. Kalay ◽  
Uriel J. Peleg
Keyword(s):  
Knowledge Based ◽  
Integrated Knowledge

Configuration Tree Solver: A Technology for Automated Design and Configuration

1990 ◽  
Author(s):  
Alexander Kott ◽  
Gerald Agin ◽  
Dave Fawcett
Keyword(s):  
Problem Solving ◽  
General Model ◽  
General Class ◽  
Domain Knowledge ◽  
Automated Design ◽  
Automotive Component ◽  
Business Operation ◽  
Knowledge Based ◽  
Specific Configuration

Abstract Configuration is a process of generating a definitive description of a product or an order that satisfies a set of specified requirements and known constraints. Knowledge-based technology is an enabling factor in automation of configuration tasks found in the business operation. In this paper, we describe a configuration technique that is well suited for configuring “decomposable” artifacts with reasonably well defined structure and constraints. This technique may be classified as a member of a general class of decompositional approaches to configuration. The domain knowledge is structured as a general model of the artifact, an and-or hierarchy of the artifact’s elements, features, and characteristics. The model includes constraints and local specialists which are attached to the elements of the and-or-tree. Given the specific configuration requirements, the problem solving engine searches for a solution, a subtree, that satisfies the requirements and the applicable constraints. We describe an application of this approach that performs configuration and design of an automotive component.

Problem solving methods and knowledge systems: A personal journey to perceptual images as knowledge

2009 ◽  
Vol 23 (4) ◽  
pp. 331-338
Author(s):  
B. Chandrasekaran
Keyword(s):  
Problem Solving ◽  
Cognitive Architecture ◽  
Mental Image ◽  
Spatial Relations ◽  
Point Of View ◽  
Design Strategies ◽  
Symbolic Form ◽  
Knowledge Based ◽  
High Level ◽  
Use Of Knowledge

AbstractI was among those who proposed problem solving methods (PSMs) in the late 1970s and early 1980s as a knowledge-level description of strategies useful in building knowledge-based systems. This paper summarizes the evolution of my ideas in the last two decades. I start with a review of the original ideas. From an artificial intelligence (AI) point of view, it is not PSMs as such, which are essentially high-level design strategies for computation, that are interesting, but PSMs associated with tasks that have a relation to AI and cognition. They are also interesting with respect to cognitive architecture proposals such as Soar and ACT-R: PSMs are observed regularities in the use of knowledge that an exclusive focus on the architecture level might miss, the latter providing no vocabulary to talk about these regularities. PSMs in the original conception are closely connected to a specific view of knowledge: symbolic expressions represented in a repository and retrieved as needed. I join critics of this view, and maintain with them that most often knowledge is not retrieved from a base as much as constructed as needed. This criticism, however, raises the question of what is in memory that is not knowledge as traditionally conceived in AI, but can support theconstructionof knowledge in predicate–symbolic form. My recent proposal about cognition and multimodality offers a possible answer. In this view, much of memory consists of perceptual and kinesthetic images, which can be recalled during deliberation and from which internal perception can generate linguistic–symbolic knowledge. For example, from a mental image of a configuration of objects, numerous sentences can be constructed describing spatial relations between the objects. My work on diagrammatic reasoning is an implemented example of how this might work. These internal perceptions on imagistic representations are a new kind of PSM.

Outcomes, Implications, and Concluding Thoughts

2017 ◽  
Author(s):  
Richard E. Ocejo
Keyword(s):  
Problem Solving ◽  
Interpersonal Communication ◽  
Culturally Relevant ◽  
New Economy ◽  
Manual Labor ◽  
Cultural Understanding ◽  
Knowledge Based ◽  
Mental Problem ◽  
Cultural Repertoires ◽  
Career Options

This concluding chapter reviews the alternative paths for how workers are dealing with conditions of the precarious new economy. They are entering common occupations in everyday workplaces that people do not normally think of as knowledge-based or culturally relevant, and transforming them into high-end, quality jobs that fuse mental and manual labor and that people with other work opportunities see as viable career options. These workers experience manual labor as meaningful and even fun through the enactment of a set of cultural repertoires that allow for physical, bodily labor, challenging mental problem-solving, cultural understanding, and interpersonal communication. The jobs also require the confident performance of each of these work practices in concert, not independently of the others.

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