Paper Info
Title
An intelligent system for driving trains using Case-Based Reasoning
Abstract
This paper presents a planning approach using Case-Based Reasoning (CBR) to generate plans for driving trains. The main idea of a planning strategy is to generate a sequence of actions for an agent, which can use these actions to change its environment. CBR allows using prior experiences in the situation assessment task. In the proposed approach, each previous experience (if not applicable) is adjusted resulting in cases specializations. Our interest is reducing the number of corrections triggered when a case retrieved is not applicable, based on these specializations. Experiments showed that the plans generated using this proposed method had a significant increase in the number of cases recovered satisfactorily, also reducing the need of adaptations for the cases recovered.
Year
DOI
Venue
2012
10.1109/ICSMC.2012.6377981
Systems, Man, and Cybernetics
Keywords
Field
DocType
case-based reasoning,planning (artificial intelligence),railways,CBR,action sequence generation,case-based reasoning,intelligent system,planning approach,planning strategy,situation assessment task,train driving,Artificial Intelligence,Case-Based Reasoning,Driving of Trains,Planning
Decision tree,Computer science,Situation analysis,Acceleration,Artificial intelligence,Train,Case-based reasoning,Maintenance engineering,Machine learning
Conference
ISSN
ISBN
Citations 
1062-922X
978-1-4673-1712-2
3
PageRank 
References 
Authors
0.52
5
6
Name
Order
Citations
PageRank
André Pinz Borges1147.67
Osmar Betazzi Dordal275.02
Denise Maria Vecino Sato383.98
Bráulio Coelho Ávila42210.63
Fabrício Enembreck527438.42
Edson Emílio Scalabrin63614.52