TY - GEN
T1 - A learning agent to assist in airline disruption management
AU - Langerman, J. J.
AU - Ehlers, E. M.
PY - 2005
Y1 - 2005
N2 - Airline disruption management, also known as airline operational scheduling, is becoming an important research topic. During the last few decades great strides have been made to generate optimal schedules. The problem is that when the ideal schedule gets disrupted on the day of operation we need to recover as quickly as possible. A combination of an expert system and a Q-Learning system, implemented as an intelligent agent can be used as a technological approach to solve this problem.
AB - Airline disruption management, also known as airline operational scheduling, is becoming an important research topic. During the last few decades great strides have been made to generate optimal schedules. The problem is that when the ideal schedule gets disrupted on the day of operation we need to recover as quickly as possible. A combination of an expert system and a Q-Learning system, implemented as an intelligent agent can be used as a technological approach to solve this problem.
UR - http://www.scopus.com/inward/record.url?scp=33847211795&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:33847211795
SN - 0769525040
SN - 9780769525044
T3 - Proceedings - International Conference on Computational Intelligence for Modelling, Control and Automation, CIMCA 2005 and International Conference on Intelligent Agents, Web Technologies and Internet
SP - 321
EP - 326
BT - Proceedings - International Conference on Computational Intelligence for Modelling, Control and Automation, CIMCA 2005 and International Conference on Intelligent Agents, Web Technologies and Internet
T2 - International Conference on Computational Intelligence for Modelling, Control and Automation, CIMCA 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, IAWTIC 2005
Y2 - 28 November 2005 through 30 November 2005
ER -