Name
Title | ||
|---|---|---|
Impact Analysis Model For Brasilia Area Control Center Using Multi-Agent System With Reinforcement Learning |
Abstract | ||
|---|---|---|
This paper describes a methodology based on multi-agent theory for Air Traffic Flow Management (ATFM) problem. We modeling a function that take account the impact of traffic managers actions, such as, fairness in the distribution of delays, and financial cost. This model is integrated with a Decision Support System Applied to Tactical Air Traffic Flow Management (SISCONFLUX). The architecture was implemented based on multi-agent system using reinforcement learning. The objective is to ensure the safety and prevent or reduce congestions in diverse sectors within the airspace compute the financial cost and impact of the delay generated on the aircraft. Experimental results using real data from Brasilia's Flight Information Region (FIR-BS) show that the delay time is 25% less than the results computed only with Graph Theory and fairness factor and financial cost can be used together with congestion data, without affecting safety and traffic flow. |
Year | Venue | Keywords |
|---|---|---|
2010 | 22ND INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING & KNOWLEDGE ENGINEERING (SEKE 2010) | multi agent system,reinforcement learning |
Field | DocType | Citations |
Industrial engineering,Systems engineering,Computer science,Multi-agent system,Area Control Center,Reinforcement learning | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antonio Carlos de Arruda Junior | 1 | 0 | 0.34 |
| Alessandro Ferreira Leite | 2 | 22 | 4.04 |
| Cícero Roberto Ferreira de Almeida | 3 | 0 | 0.34 |
| Alba Cristina Magalhaes Alves De Melo | 4 | 253 | 33.90 |
| Li Weigang | 5 | 13 | 3.35 |