Fetching the paper…
Reading the bibliography…
Travel planning is a complex task that involves generating a sequence of actions related to visiting places subject to constraints and maximizing some user satisfaction criteria.
A survey on case-based planning
Spalzzi, L. 2001 · 2001
Earlier work this paper cites.
PDDL2.1: An extension to PDDL for expressing temporal planning domains
Fox, M.; and Long, D. 2003 · 2003
Earlier work this paper cites.
Designing recommender systems for tourism
Berka, T.; and Plößnig, M. 2004 · 2004
Earlier work this paper cites.
Preferences and Soft Constraints in PDDL3
Gerevini, A.; and Long, D. 2006 · 2006
Earlier work this paper cites.
New Complexity Results for Classical Planning Benchmarks
Helmert, M. 2006 · 2006
Earlier work this paper cites.
Case-based travel recommendations
Ricci, F.; Cavada, D.; Mirzadeh, N.; Venturini, A.; et al. 2006 · 2006
Earlier work this paper cites.
SAMAP. A user-oriented adaptive system for planning tourist visits
Castillo, L.; Armengol, E.; Onaindía, E.; Sebastiá, L.; González-Boticario, J.; Rodríguez, A.; Fernández, S.; Arias, J. D.; and Borrajo, D. 2008 · 2008
Earlier work this paper cites.
Soft goals can be compiled away
Keyder, E.; and Geffner, H. 2009 · 2009
Earlier work this paper cites.
e-Tourism: A tourist recommendation and planning application
Sebastia, L.; Garcia, I.; Onaindia, E.; and Guzman, C. 2009 · 2009
Earlier work this paper cites.
The City Trip Planner: An expert system for tourists
Vansteenwegen, P.; Souffriau, W.; Berghe, G. V.; and Oudheusden, D. V. 2011 · 2011
Earlier work this paper cites.
A temporal constraint based planning approach for city tour and travel plan generation
Bhowmick, P. K.; Dey, S.; Samantaray, A.; Mukherjee, D.; and Misra, P. 2012 · 2012
Earlier work this paper cites.
A hybrid recommendation approach for a tourism system
Lucas, J. P.; Luz, N.; Moreno, M. N.; Anacleto, R.; Figueiredo, A. A.; and Martins, C. 2012 · 2012
Earlier work this paper cites.
On the tour planning problem
Zhu, C.; Hu, J.-Q.; Wang, F.; Xu, Y.; and Cao, R. 2012 · 2012
Earlier work this paper cites.
Sigtur/e-destination: ontology-based personalized recommendation of tourism and leisure activities
Moreno, A.; Valls, A.; Isern, D.; Marin, L.; and Borràs, J. 2013 · 2013
Earlier work this paper cites.
GAT: Platform for automatic context-aware mobile services for m-tourism
Rodriguez-Sanchez, M.; Martinez-Romo, J.; Borromeo, S.; and Hernandez-Tamames, J. 2013 · 2013
Cited alongside, same era.
Automatic Itinerary Planning for Traveling Services
Chen, G.; Wu, S.; Zhou, J.; and Tung, A. K. 2014 · 2014
Cited alongside, same era.
A survey on algorithmic approaches for solving tourist trip design problems
Gavalas, D.; Konstantopoulos, C.; Mastakas, K.; and Pantziou, G. 2014 · 2014
Cited alongside, same era.
A system for mining interesting tourist locations and travel sequences from public geo-tagged photos
Majid, A.; Chen, L.; Mirza, H. T.; Hussain, I.; and Chen, G. 2014 · 2014
Cited alongside, same era.
AI-MIX: Using Automated Planning to Steer Human Workers Towards Better Crowdsourced Plans
Manikonda, L.; Chakraborti, T.; De, S.; Talamadupula, K.; and Kambhampati, S. 2014 · 2014
Cited alongside, same era.
Autonomous travel decision-making: An early glimpse into ChatGPT and generative AI
Wong, I. A.; Lian, Q. L.; and Sun, D. 2023 · 2023
Later among the works it cites.
Google Places API
Google. 2023 · 2024
Closest in time.
Robust Planning with LLM-Modulo Framework: Case Study in Travel Planning
Gundawar, A.; Verma, M.; Guan, L.; Valmeekam, K.; Bhambri, S.; and Kambhampati, S. 2024 · 2024
Closest in time.
A survey on personalized itinerary recommendation: From optimisation to deep learning
Halder, S.; Lim, K. H.; Chan, J.; and Zhang, X. 2024 · 2024
Closest in time.
Large Language Models Can Plan Your Travels Rigorously with Formal Verification Tools
Hao, Y.; Chen, Y.; Zhang, Y.; and Fan, C. 2024 · 2024
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Brilhante, I. R.; de Macêdo, J. A. F.; Nardini, F. M.; Perego, R.; and Renso, C. 2015 · 2015
Cited alongside, same era.
Planning for Tourism Routes using Social Networks
Cenamor, I.; Núñez, S.; de la Rosa, T.; and Borrajo, D. 2017 · 2017
Cited alongside, same era.
Improving itinerary recommendations for tourists through metaheuristic algorithms: an optimization proposal
Tenemaza, M.; Luján-Mora, S.; De Antonio, A.; and Ramirez, J. 2020 · 2020
Cited alongside, same era.
Unified Planning: A Python Library Making Planning Technology Accessible
Micheli, A.; Arnold, A.; Bit-Monnot, A.; Bonassi, L.; Framba, L.; Gerevini, A.; Satchi, S. H. S.; Helmert, M.; Ingrand, F.; Iocchi, L.; Kockemann, U.; Lima, O.; Patrizi, F.; Pecora, F.; Poveda, G.; Roger, G.; Saetti, A.; Saffiotti, A.; Scala, E.; Serina, I.; Stock, S.; Teitchteil-Koenigsbuch, F.; Trapasso, A.; Traverso, P.; and Valentini, A. 2022 · 2022
Cited alongside, same era.
Achiam, J.; Adler, S.; Agarwal, S.; Ahmad, L.; Akkaya, I.; Aleman, F. L.; Almeida, D.; Altenschmidt, J.; Altman, S.; Anadkat, S.; et al. 2023 · 2023
Cited alongside, same era.
Leveraging pre-trained large language models to construct and utilize world models for model-based task planning
Guan, L.; Valmeekam, K.; Sreedharan, S.; and Kambhampati, S. 2023 · 2023
Cited alongside, same era.
Llm+ p: Empowering large language models with optimal planning proficiency
Liu, B.; Jiang, Y.; Zhang, X.; Liu, Q.; Zhang, S.; Biswas, J.; and Stone, P. 2023 · 2023
Cited alongside, same era.
Kambhampati, S. 2024 · 2024
Closest in time.
LLMs Can’t Plan, But Can Help Planning in LLM-Modulo Frameworks
Kambhampati, S.; Valmeekam, K.; Guan, L.; Stechly, K.; Verma, M.; Bhambri, S.; Saldyt, L.; and Murthy, A. 2024 · 2024
Closest in time.
Large Language Models as Planning Domain Generators
Oswald, J.; Srinivas, K.; Kokel, H.; Lee, J.; Katz, M.; and Sohrabi, S. 2024 · 2024
Closest in time.
Pallagani, V.; Roy, K.; Muppasani, B.; Fabiano, F.; Loreggia, A.; Murugesan, K.; Srivastava, B.; Rossi, F.; Horesh, L.; and Sheth, A. 2024 · 2024
Closest in time.
Generalized planning in pddl domains with pretrained large language models
Silver, T.; Dan, S.; Srinivas, K.; Tenenbaum, J. B.; Kaelbling, L.; and Katz, M. 2024 · 2024
Closest in time.
The Use of Generative Search Engines for Knowledge Work and Complex Tasks
Suri, S.; Counts, S.; Wang, L.; Chen, C.; Wan, M.; Safavi, T.; Neville, J.; Shah, C.; White, R. W.; Andersen, R.; et al. 2024 · 2024
Closest in time.
Travelplanner: A benchmark for real-world planning with language agents
Xie, J.; Zhang, K.; Chen, J.; Zhu, T.; Lou, R.; Tian, Y.; Xiao, Y.; and Su, Y. 2024 · 2024
Closest in time.
NATURAL PLAN: Benchmarking LLMs on Natural Language Planning
Zheng, H. S.; Mishra, S.; Zhang, H.; Chen, X.; Chen, M.; Nova, A.; Hou, L.; Cheng, H.-T.; Le, Q. V.; Chi, E. H.; et al. 2024 · 2024
Closest in time.