Name
Abstract | ||
|---|---|---|
This paper presents a planning approach using Case-Based Reasoning (CBR) modeled as a Subsumption Architecture 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 for new task assignments. In the proposed ap-proach, each previous experience (if not applicable) is adjusted us-ing one or more adaptation methods like substitutive and genetic algorithm. Our interest is to create a flexible architecture for an agent and apply it to simulate train conductions. We expect that the plans generated by this approach generate better results com-pared to another studies already developed for the area mainly considering fuel consumption and travel time. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/CSCWD.2014.6846811 | CSCWD |
Keywords | Field | DocType |
subsumption architecture,case based reasoning,acceleration,genetic algorithm,planning,genetic algorithms,railway engineering,artificial intelligence,fuel consumption,force | Architecture,Multi layer,Computer science,Fuel efficiency,Subsumption architecture,Travel time,Train,Genetic algorithm,Distributed computing | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| André Pinz Borges | 1 | 14 | 7.67 |
| Osmar Betazzi Dordal | 2 | 7 | 5.02 |
| Denise Maria Vecino Sato | 3 | 8 | 3.98 |
| Bráulio Coelho Ávila | 4 | 22 | 10.63 |
| Fabrício Enembreck | 5 | 274 | 38.42 |
| Edson Emílio Scalabrin | 6 | 36 | 14.52 |
| Richardson Ribeiro | 7 | 43 | 11.12 |