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Distributed case-based reasoning
The Knowledge Engineering Review, 2005Distribution of resources within case-based reasoning (CBR) architectures is beneficial in a variety of application contexts. This article briefly discusses some of the approaches that fall under the heading of distributed CBR, and their general impact.
Enric Plaza, Lorraine McGinty
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FROM CASE-BASED REASONING TO TRACES-BASED REASONING
IFAC Proceedings Volumes, 2006Abstract CBR is an original paradigm to adapt solutions of past problems in order to solve new similar problems. A case is a problem with its solution and cases are stored in a case library. The reasoning process obeys to a cycle allowing to “learn” from new solved cases.
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Holographic Case-Based Reasoning
2020In this paper, we present a novel extension of CBR that allows cases to be more proactive at problem solving, by enriching case representations and facilitating richer interconnectedness between cases. We empirically study the improvements resulting from a holographic realization on experimental datasets.
Devi Ganesan, Sutanu Chakraborti
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The Knowledge Engineering Review, 2005
A primary research stream that contributed to the birth of case-based reasoning (CBR) was Artificial Intelligence and Law. Since law is largely about cases, it is a particularly interesting domain for CBR researchers. This article surveys some of the historically significant systems and developments in this field.
Rissland, EL, Ashley, KD, Branting, LK
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A primary research stream that contributed to the birth of case-based reasoning (CBR) was Artificial Intelligence and Law. Since law is largely about cases, it is a particularly interesting domain for CBR researchers. This article surveys some of the historically significant systems and developments in this field.
Rissland, EL, Ashley, KD, Branting, LK
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Cooperative Case-based Reasoning
1997We are investigating possible modes of cooperation among homogeneous agents with learning capabilities. In this paper we will be focused on agents that learn and solve problems using Case-based Reasoning (CBR), and we will present two modes of cooperation among them: Distributed Case-based Reasoning (DistCBR) and Collective Case-based Reasoning (ColCBR)
Enric Plaza +2 more
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Case-based reasoning foundations
The Knowledge Engineering Review, 2005A basic observation is that case-based reasoning has roots in different disciplines: cognitive science, knowledge representation and processing, machine learning and mathematics. As a consequence, there are foundational aspects from each of these areas. We briefly discuss them and comment on the relations between these types of foundations.
Michael M. Richter, Agnar Aamodt
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2001
This chapter contains an overview of Case-Based Reasoning (CBR). The main goal is to have a balance between brevity and expressiveness and to provide helpful pointers to literature in the field. To do so, we first describe the CBR types and the CBR cycle, then we briefly review a representative set of systems, next we discuss the connections between ...
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This chapter contains an overview of Case-Based Reasoning (CBR). The main goal is to have a balance between brevity and expressiveness and to provide helpful pointers to literature in the field. To do so, we first describe the CBR types and the CBR cycle, then we briefly review a representative set of systems, next we discuss the connections between ...
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Integrations with case-based reasoning
The Knowledge Engineering Review, 2005This commentary succinctly summarizes work in integrating case-based reasoning (CBR) with other reasoning modalities. Including CBR in mixed mode approaches promotes synergies and benefits beyond those achievable using CBR or other individual reasoning approaches alone.
Marling, C, Rissland, E, Aamodt, A
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The Knowledge Engineering Review, 2005
This commentary provides a definition of textual case-based reasoning (TCBR) and surveys research contributions according to four research questions. We also describe how TCBR can be distinguished from text mining and information retrieval. We conclude with potential directions for TCBR research.
Rosina O. Weber +2 more
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This commentary provides a definition of textual case-based reasoning (TCBR) and surveys research contributions according to four research questions. We also describe how TCBR can be distinguished from text mining and information retrieval. We conclude with potential directions for TCBR research.
Rosina O. Weber +2 more
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Case-Based Reasoning with Confidence
2000A case-based reasoning system can produce both a solution and an estimate of the confidence in that solution. The confidence value can be used to determine whether the solution does or does not have the needed accuracy. A statistical method can be used to compute a confidence value from information generated during the case-based reasoning process ...
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