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Knowledge Acquisition for Configuration Tasks : The EXPECT Approach

Surya Ramachandran, Yolanda Gil

Open publisher page 3 citations

Abstract

Configuration systems often use large and complex knowledge bases that need to be maintained and extended over time. The explicit representation of problem-solving knowledge and factual knowledge can greatly enhance the role of a knowledge acquisition tool by deriving from the current knowledge base, the knowledge gaps that must be resolved. This paper details EXPECT’s approach to knowledge acquisition in the configuration domain using the propose-and-revise strategy as an example. EXPECT supports users in a variety of KA tasks like filling knowledge roles, making modifications to the knowledge base including entering new components, classes and even adapting problem-solving strategies for new tasks. EXPECT’s guidance changes as the knowledge base changes, providing a more flexible approach to knowledge acquisition. The paper also examines the possible use of EXPECT as a KA tool in the complex and real world domain of computer configuration.

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What this paper is about

Configuration systems often use large and complex knowledge bases that need to be maintained and extended over time. The explicit representation of problem-solving knowledge and factual knowledge can greatly enhance the role of a knowledge acquisition tool by deriving from the current knowledge base, the knowledge gaps that must be resolved. This paper details EXPECT’s approach to knowledge acquisition in the configuration domain using the propose-and-revise strategy as an example. EXPECT supports users in a variety of KA tasks like filling knowledge roles, making modifications to the knowledge base including entering new components, classes and even adapting problem-solving strategies for new tasks. EXPECT’s guidance changes as the knowledge base changes, providing a more flexible approach to knowledge acquisition. The paper also examines the possible use of EXPECT as a KA tool in the complex and real world domain of computer configuration.

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Available abstract

Configuration systems often use large and complex knowledge bases that need to be maintained and extended over time. The explicit representation of problem-solving knowledge and factual knowledge can greatly enhance the role of a knowledge acquisition tool by deriving from the current knowledge base, the knowledge gaps that must be resolved. This paper details EXPECT’s approach to knowledge acquisition in the configuration domain using the propose-and-revise strategy as an example. EXPECT supports users in a variety of KA tasks like filling knowledge roles, making modifications to the knowledge base including entering new components, classes and even adapting problem-solving strategies for new tasks. EXPECT’s guidance changes as the knowledge base changes, providing a more flexible approach to knowledge acquisition. The paper also examines the possible use of EXPECT as a KA tool in the complex and real world domain of computer configuration.

Key concepts: Knowledge base, Domain knowledge, Knowledge acquisition, Computer science, Open Knowledge Base Connectivity, Knowledge-based systems, Variety (cybernetics), Procedural knowledge

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