Knowledge Reuse Method to Improve the Learning of Interference-Preventive Allocation Policies in Multi-Car Elevators

Design reuse is the application of past designs knowledge and successful experience to current design process and it is a significant method for rapid design. A knowledge-reuse-based rapid product design model is proposed and a three-factor product design iterative process model is studied. Finally, it is applied successfully in the rapid product design of construction machinery combining with the requirement of the construct machinery product design.

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A process for knowledge reuse in communities of practice of e-learning

Procedia - Social and Behavioral Sciences ◽

10.1016/j.sbspro.2010.03.707 ◽

2010 ◽

Vol 2 (2) ◽

pp. 4436-4443 ◽

Cited By ~ 10

Author(s):

Lamia Berkani ◽

Azeddine Chikh

Keyword(s):

Communities Of Practice ◽

Knowledge Reuse ◽

E Learning

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Knowledge Reuse in Mass Customization of Knowledge-Intensive Services

Artificial Intelligence in Economics and Managment ◽

10.1007/978-1-4613-1427-1_8 ◽

1996 ◽

pp. 107-127 ◽

Cited By ~ 1

Author(s):

Michel Benaroch

Keyword(s):

Mass Customization ◽

Knowledge Reuse ◽

Knowledge Intensive

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Collaborative Case-Based Reasoning for Knowledge Discovery of Elders Health Assessment System

The Open Biomedical Engineering Journal ◽

10.2174/1874120701408010068 ◽

2014 ◽

Vol 8 (1) ◽

pp. 68-74 ◽

Cited By ~ 3

Author(s):

Ping Hu ◽

Dong-xiao Gu ◽

Yu Zhu

Keyword(s):

Single Case ◽

Health Assessment ◽

Assessment System ◽

Gray Relational Analysis ◽

Retrieval Algorithm ◽

Case Based Reasoning ◽

Knowledge Reuse ◽

Case Retrieval ◽

Case Library ◽

Case Representation

The existing Elders Health Assessment (EHA) system based on single-case-library reasoning has low intelligence level, poor coordination, and limited capabilities of assessment decision support. To effectively support knowledge reuse of EHA system, this paper proposes collaborative case reasoning and applies it to the whole knowledge reuse process of EHA system. It proposes a multi-case library reasoning application framework of EHA knowledge reuse system, and studies key techniques such as case representation, case retrieval algorithm, case optimization and correction, and reuse etc.. In the aspect of case representation, XML-based multi-case representation for case organization and storage is applied to facilitate case retrieval and management. In the aspect of retrieval method, Knowledge-Guided Approach with Nearest-Neighbor is proposed. Given the complexity of EHA, Gray Relational Analysis with weighted Euclidean Distance is used to measure the similarity so as to improve case retrieval accuracy.

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Methods and Algorithms for Knowledge Reuse in Multiagent Reinforcement Learning

10.5753/ctd.2020.11360 ◽

2020 ◽

Author(s):

Felipe Leno Da Silva ◽

Anna Helena Reali Costa

Keyword(s):

Reinforcement Learning ◽

Transfer Learning ◽

Learning Process ◽

Trial And Error ◽

Knowledge Reuse ◽

Previous Knowledge ◽

Learning Methods ◽

Types Of Knowledge ◽

Learning Agent ◽

Multiagent Reinforcement Learning

Reinforcement Learning (RL) is a powerful tool that has been used to solve increasingly complex tasks. RL operates through repeated interactions of the learning agent with the environment, via trial and error. However, this learning process is extremely slow, requiring many interactions. In this thesis, we leverage previous knowledge so as to accelerate learning in multiagent RL problems. We propose knowledge reuse both from previous tasks and from other agents. Several flexible methods are introduced so that each of these two types of knowledge reuse is possible. This thesis adds important steps towards more flexible and broadly applicable multiagent transfer learning methods.

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