Abstract
Buying airline tickets is an ubiquitous task in which it is difficult for humans to minimize cost due to insufficient information. Even with historical data available for inspection (a recent addition to some travel reservation websites), it is difficult to assess how purchase timing translates into changes in expected cost. To address this problem, we introduce an agent which is able to optimize purchase timing on behalf of customers. We provide results that demonstrate the method can perform much closer to the optimal purchase policy than existing decision theoretic approaches for this domain.
Original language | English (US) |
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Title of host publication | 12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013 |
Publisher | International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS) |
Pages | 1341-1342 |
Number of pages | 2 |
Volume | 2 |
State | Published - Jan 1 2013 |
Event | 12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013 - Saint Paul, MN, United States Duration: May 6 2013 → May 10 2013 |
Other
Other | 12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013 |
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Country/Territory | United States |
City | Saint Paul, MN |
Period | 5/6/13 → 5/10/13 |
Keywords
- Airline ticket prices
- Feature selection
- PLS regression