Selection of behavioral parameters: integration of discontinuous switching via case-based reasoning with continuous adaptation via learning momentum

2003 ◽  
Author(s):  
J.B. Lee ◽  
M. Likhachev ◽  
R.C. Arkin
Keyword(s):  
Case Based Reasoning ◽  
Behavioral Parameters ◽  
Case Based ◽  
Selection Of

A Case Based Reasoning System For Recommendation Of Restaurant In Jimbaran Using K-Nearest Neighbor

2020 ◽  
Vol 9 (2) ◽  
pp. 267
Author(s):  
I Gede Teguh Mahardika ◽  
I Wayan Supriana
Keyword(s):  
Recommendation System ◽  
Nearest Neighbor ◽  
Case Based Reasoning ◽  
Retrieval Process ◽  
K Nearest Neighbor ◽  
Reasoning System ◽  
Human Ability ◽  
And Function ◽  
Case Based ◽  
Selection Of

Culinary is one of the favorite businesses today. The number of considerations to choose a restaurant or place to visit becomes one of the factors that is difficult to determine the restaurant or place to eat. To get the desired place to eat advice, one needs a recommendation system. Decisions made by the recommendation system can be used as a reference to determine the choice of restaurants. One method that can be used to build a recommendation system is Case Based Reasoning. The Case Based Reasoning (CBR) method mimics human ability to solve a problem or cases. The retrieval process is the most important stage, because at this stage the search for a solution for a new case is carried out. The study used the K-Nearest Neighbor method to find closeness between new cases and case bases. With the selection of features used as domains in the system, the results of recommendations presented can be more suggestive and accurate. The system successfully provides complex recommendations based on the type and type of food entered by the user. Based on blackbox testing, the system has features that can be used and function properly according to the purpose of creating the system.

scholarly journals Playing with Cases: Rendering Expressive Music with Case-Based Reasoning

AI Magazine ◽  
2012 ◽  
Vol 33 (4) ◽  
pp. 22 ◽  
Author(s):  
Ramon López de Mántaras
Keyword(s):  
Music Performance ◽  
Fundamental Aspect ◽  
Memorial Lecture ◽  
Case Based Reasoning ◽  
Reasoning System ◽  
Audio Recordings ◽  
Significant Research ◽  
Audio Information ◽  
Case Based ◽  
Selection Of

This paper surveys significant research on the problem of rendering expressive music by means of AI techniques with an emphasis on Case-Based Reasoning. Following a brief overview discussing why we prefer listening to expressive music instead of lifeless synthesized music, we examine a representative selection of well-known approaches to expressive computer music performance with an emphasis on AI-related approaches. In the main part of the paper we focus on the existing CBR approaches to the problem of synthesizing expressive music, and particularly on TempoExpress, a case-based reasoning system developed at our Institute, for applying musically acceptable tempo transformations to monophonic audio recordings of musical performances. Finally we briefly describe an ongoing extension of our previous work consisting on complementing audio information with information of the gestures of the musician. Music is played through our bodies, therefore capturing the gesture of the performer is a fundamental aspect that has to be taken into account in future expressive music renderings. This paper is based on the “2011 Robert S. Engelmore Memorial Lecture” given by the first author at AAAI/IAAI 2011.

Applicability of Case-Based Reasoning for Selection of Cyanide-Free Gold Leaching Methods

2016 ◽  
pp. 249-264 ◽  
Author(s):  
Maria Leikola ◽  
Lotta Rintala ◽  
Christian Sauer ◽  
Thomas Roth-Berghofer ◽  
Mari Lundström
Keyword(s):  
Case Based Reasoning ◽  
Gold Leaching ◽  
Free Gold ◽  
Leaching Methods ◽  
Case Based ◽  
Selection Of

Selection of internals for reactive distillation column—case-based reasoning approach

2004 ◽  
Vol 28 (1-2) ◽  
pp. 37-44 ◽  
Author(s):  
Yuri Avramenko ◽  
Lars Nyström ◽  
Andrzej Kraslawski
Keyword(s):  
Distillation Column ◽  
Reactive Distillation ◽  
Case Based Reasoning ◽  
Case Based ◽  
Selection Of

A case-based reasoning approach to the selection of comparable evidence for retail rent determination

1997 ◽  
Vol 12 (4) ◽  
pp. 417-428 ◽  
Author(s):  
Brenna O'Roarty ◽  
David Patterson ◽  
Stanley McGreal ◽  
Alastair Adair
Keyword(s):  
Case Based Reasoning ◽  
Case Based ◽  
Selection Of

scholarly journals Retrieval, reuse, revision and retention in case-based reasoning

2005 ◽  
Vol 20 (3) ◽  
pp. 215-240 ◽  
Author(s):  
RAMON LOPEZ DE MANTARAS ◽  
DAVID MCSHERRY ◽  
DEREK BRIDGE ◽  
DAVID LEAKE ◽  
BARRY SMYTH ◽  
...  
Keyword(s):  
Problem Solving ◽  
Analogical Reasoning ◽  
Case Based Reasoning ◽  
The Past ◽  
Future Problem ◽  
Considerable Success ◽  
Representative Selection ◽  
Case Based ◽  
Selection Of

Case-based reasoning (CBR) is an approach to problem solving that emphasizes the role of prior experience during future problem solving (i.e., new problems are solved by reusing and if necessary adapting the solutions to similar problems that were solved in the past). It has enjoyed considerable success in a wide variety of problem solving tasks and domains. Following a brief overview of the traditional problem-solving cycle in CBR, we examine the cognitive science foundations of CBR and its relationship to analogical reasoning. We then review a representative selection of CBR research in the past few decades on aspects of retrieval, reuse, revision and retention.

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