10 edition of Planning and learning by analogical reasoning found in the catalog.
Published
1994
by Springer-Verlag in Berlin, New York
.
Written in English
Edition Notes
Includes bibliographical references (p. [173]-181).
| Statement | Manuela M. Veloso. |
| Series | Lecture notes in artificial intelligence ;, 886., Lecture notes in computer science, Lecture notes in computer science., Lecture notes in computer science ;, 886. |
| Classifications | |
|---|---|
| LC Classifications | Q325.5 .V45 1994 |
| The Physical Object | |
| Pagination | xiii, 181 p. : |
| Number of Pages | 181 |
| ID Numbers | |
| Open Library | OL1117778M |
| ISBN 10 | 3540588116, 0387588116 |
| LC Control Number | 94043959 |
Analogical reasoning theory provides a foundation for metaphor-enhanced design of multisensory representations. Analogists have established that people learn from mapping relational structure from one domain to another (Gentner, ; Gentner & Markman, ; Holyoak, Gentner, & Kokinov, ). This paper describes the integration of analogical reasoning into general problem solving as a method of learning at the strategy level to solve problems more : Manuela Veloso.
The first definition of analogy came from Aristotle. He defined an analogy as “an equality of proportions involving at least 4 terms when the second is related to the first as the fourth is to the third” (Aristotle, Metaphysics).This type of “classical” analogy is still used in intelligence testing, and is called the item analogy. The strength of analogical reasoning in biology lies in the common evolutionary origin of homologous structures and systems, within and between organisms. For example, the many members of the hemoglobin family, which transport oxygen in vertebrate blood, are all .
To learn more or modify/prevent or through reasoning by analogy to similar problems solved in the past. Planning and problem solving depend on the hierarchical organization of action and Author: Robert G Morrison. Many standardized tests-including high school entrance exams, SATs, civil service exams, GREs, LSATS, and others-use analogy questions to test both logic and reasoning skills and word knowledge. Word Analogy Questions is designed to help students prepare for the verbal and reasoning sections of these and other assessment and entrance exams/5(11).
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About this book This research monograph describes the integration of analogical and case-based reasoning into general problem solving and planning as a method of speedup learning. The method, based on derivational analogy, has been fully implemented in PRODIGY/ANALOGY and proven in practice to be amenable to scaling up, both in terms of domain.
This research monograph describes the integration of analogical and case-based reasoning into general problem solving and planning as a method of speedup learning. The method, based on derivational analogy, has been fully implemented in PRODIGY/ANALOGY and proven in practice to be amenable to scaling up, both in terms of domain and problem by: This research monograph describes the integration of analogical and case-based reasoning into general problem solving and planning as a method of speedup learning.
The method, based on derivational analogy, has been fully implemented in PRODIGY/ANALOGY and proven in practice to be amenable to scaling up, both in terms of domain and problem complexity. This research monograph describes the integration of analogical and case-based reasoning into general problem solving and planning as a method of speedup learning.
The method, based on derivational analogy, has been fully implemented in PRODIGY/ANALOGY and proven in Price: $ Planning and learning by analogical reasoning.
[Manuela M Veloso] -- "This research monograph describes the integration of analogical and case-based reasoning into general problem solving and planning as a method of speedup learning. This research monograph describes the integration of analogical and case-based reasoning into general problem solving and planning as a method of speedup learning.
Planning and Learning by Analogical Reasoning Manuela Veloso Springer Verlag, December (This is a book publication of my PhD thesis document.) Derivational Analogy in PRODIGY: Automating Case Acquisition, Storage, and Utilization Manuela M.
Veloso and Jaime G. Carbonell Machine Learning, 10, This research monograph describes the integration of analogical and case-based reasoning into general problem solving and planning as a method of speedup learning.
The method, based on derivational analogy, has been fully implemented in PRODIGY/ANALOGY and proven in practice to be amenable to scaling up, both in terms of domain and problem complexity.
In this work, the strategy-level learning. This dissertation integrates derivational analogy into general problem solving as a method of learning at the strategy level to solve problems more effectively. The derivational analogy method has been fully implemented in the sc PRODIGY architecture and proven empirically to be amenable to scaling up both in terms of domain and problem complexity.
Explaining Effective Learning by Analogical Reasoning Helmar Gust ([email protected]) Institute of Cognitive Science, University of Osnabr¨uck Albrechtstr.
28, Osnabr¨uck, Germany Kai-Uwe Kuhnberger ([email protected])¨ Institute of Cognitive Science, University of Osnabr¨uck Albrechtstr. 28, Osnabr¨uck, Germany AbstractFile Size: 74KB. Part of the Symbolic Computation book series (SYMBOLIC) Analogical reasoning is a powerful mechanism for exploiting past experience in planning and problem solving.
This chapter outlines a theory of analogical problem solving based on an extension to means-ends by: MIND,BRAIN,ANDEDUCATION Analogical Reasoning in the Classroom: Insights From Cognitive Science Michael S. Vendetti1, Bryan J. Matlen2, Lindsey E. Richland3, and Silvia A.
Bunge1 ABSTRACT—Applying knowledge from one context toFile Size: KB. Mathematical and Analogical Reasoning of Young Learners provides foundational knowledge of the nature, development, and assessment of mathematical and analogical reasoning in young children.
Reasoning is fundamental to understanding mathematics and is identified as one of the 10 key standards for school mathematics for the new millennium. Analogical reasoning is a powerful mechanism for exploiting past experience in planning and problem solving.
This chapter outlines a theory of analogical problem solving based on an extension to. Its contribution to cognition has been defined in varying ways. So is a third aspect of analogical reasoning, the creative aspect.
Put simply, analogy is part of how mathematicians think. Analogy is also an important part of how young children think. Goswami, ,for overviews). This book focusses on inductive program synthesis, and especially on the induction of recursive functions; it is organized into three parts on planning, inductive program synthesis, and analogical problem solving and learning.
Cite this chapter as: () Analogical replay. In: Veloso M.M. (eds) Planning and Learning by Analogical Reasoning. Lecture Notes in Computer Science (Lecture Notes in.
The selection first takes a look at the automated reuse of design plans in BOGART and ARGO, an analogical reasoning system for solving design problems. Topics include analogy mechanisms in ARGO, analogical reasoning and learning, ARGO development environment, using VEXED to construct a design plan, and how BOGART reuses a design plan.
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Integrating Planning, Learning, and Analogy. A Prototype System this induction process can be performed by an analogical reasoning module. My reason for discussing Skinner's book in such. Book Description. Mathematical and Analogical Reasoning of Young Learners provides foundational knowledge of the nature, development, and assessment of mathematical and analogical reasoning in young children.
Reasoning is fundamental to understanding mathematics and is identified as one of the 10 key standards for school mathematics for the new millennium.COLLEGE OF ENGINEERING AND TECHNOLOGY, Explanation-based Learning, Discovery, Analogy, Formal Learning Theory, Neural Net Learning and Genetic Learning.
Expert Systems: Representing and Using Domain Knowledge, Expert studied by AI include perception, communicational using human languages, reasoning, planning, learning and memory.5 LEARNING BY ANALOGY: FORMULATING AND GENERALIZING PLANS FROM PAST EXPERIENCE Jaime G. Carbonell Carnegie-Mellon University ABSTRACT Analogical reasoning is a powerful mechanism for exploiting past experience in planning and problem solving.
This chapter outlines a theory of analogical problem solving based on an extension to means-ends by:
