Predicting bundles of spatial locations from learning revealed preference data

Truc Viet Le, Siyuan Liu, Hoong Chuin Lau, Ramayya Krishnan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

We propose the problem of predicting a bundle of goods, where the goods considered is a set of spatial locations that an agent wishes to visit. This typically arises in the tourism setting where attractions can often be bundled and sold as a package to visitors. While the problem of predicting future locations given the current and past trajectories is wellestablished, we take a radical approach by looking at it from an economic point of view. We view an agent's past trajectories as revealed preference (RP) data, where the choice of locations is a solution to an optimisation problem according to some unknown utility function and subject to the prevailing prices and budget constraint. We approximate the prices and budget constraint as the time costs to finish visiting the chosen locations. We leverage on a recent line of work that has established algorithms to efficiently learn from RP data (i.e., recover the utility functions) and make predictions of future purchasing behaviours. We adopt and adapt those work to our original setting while incorporating techniques from spatiotemporal analysis. We experiment with real-world trajectory data collected from a theme park. Our predictions show improved accuracies in comparison with the baseline methods by at least 20%, one of which comes from the spatiotemporal analysis domain.

Original languageEnglish (US)
Title of host publicationAAMAS 2015 - Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1121-1129
Number of pages9
Volume2
ISBN (Electronic)9781450337700
StatePublished - 2015
Event14th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015 - Istanbul, Turkey
Duration: May 4 2015May 8 2015

Other

Other14th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015
CountryTurkey
CityIstanbul
Period5/4/155/8/15

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Trajectories
Purchasing
Economics
Costs
Experiments

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

Cite this

Le, T. V., Liu, S., Lau, H. C., & Krishnan, R. (2015). Predicting bundles of spatial locations from learning revealed preference data. In AAMAS 2015 - Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (Vol. 2, pp. 1121-1129). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).
Le, Truc Viet ; Liu, Siyuan ; Lau, Hoong Chuin ; Krishnan, Ramayya. / Predicting bundles of spatial locations from learning revealed preference data. AAMAS 2015 - Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems. Vol. 2 International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2015. pp. 1121-1129
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Le, TV, Liu, S, Lau, HC & Krishnan, R 2015, Predicting bundles of spatial locations from learning revealed preference data. in AAMAS 2015 - Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems. vol. 2, International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), pp. 1121-1129, 14th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015, Istanbul, Turkey, 5/4/15.

Predicting bundles of spatial locations from learning revealed preference data. / Le, Truc Viet; Liu, Siyuan; Lau, Hoong Chuin; Krishnan, Ramayya.

AAMAS 2015 - Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems. Vol. 2 International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2015. p. 1121-1129.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Le TV, Liu S, Lau HC, Krishnan R. Predicting bundles of spatial locations from learning revealed preference data. In AAMAS 2015 - Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems. Vol. 2. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). 2015. p. 1121-1129