Abstract
Automatically generating high-quality routes using real map data is difficult for a number of reasons. Real maps rarely contain the sort of information that is useful for constructing high quality routes. In addition, the notion of “route quality” is difficult to define and is likely to change from person to person. In this sense the automatic construction of high-quality routes that match the preferences of individuals is an example of a weak-theory problem, and therefore well suited to a case-based approach. In this paper we describe and evaluate a case-based route planning system that is capable of efficiently generating routes that reflect the implicit preferences of individual users.
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References
Branting, L. and Aha, D.: Stratified Case-Based Reasoning: Reusing hierarchical problem solving episodes, Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, Morgan Kaufmann, 1995, pp. 384–390.
Haigh, K., Shewchuk, J., and Veloso, M.: Exploiting Domain Geometry in Analogical Route Planning, Journal of Experimental and Theoretical Artificial Intelligence 9 (1997), 509–541.
Haigh, K. and Veloso, M.: Route Planning by Analogy, Proceedings of the International Conference of Case-Based Reasoning, Springer-Verlag, 1995, pp. 169–180.
Kolodner, J. (ed.): Case-Based Reasoning, Morgan Kaufmann, 1993.
Liu, B.: Using Knowledge To Isolate Search in Route Finding, Proceedings of Fourteenth International Joint Conference on Artificial Intelligence, 1995, pp. 119–124.
Liu, B.: Intelligent Route Finding: Combining Knowledge, Cases and An Efficient Search Algorithm, Proceedings of the 12th European Conference on Artificial Intelligence, 1996, pp. 380–384.
Rogers, S., and Fiechter, C.: A Route Advice Agent that Models Driver Preferences, Proceedings of the American Association of Artificial Intelligence Spring Symposium on Agents with Adjustable Autonomy, 1999, pp. 106–113.
Rogers, S., and Langley, P.: Personalized Driving Route Recommendations, Proceedings of the American Association of Artificial Intelligence Workshop on Recommender Systems, 1998, pp. 96–100.
Smyth, B. and Cunningham, P.: The Utility Problem Analysed: A Case-Based Reasoning Perspective, Proceedings of the American Association of Artificial Intelligence Spring Symposium on Agents with Adjustable Autonomy (I. Smith and B. Faltings, eds.), Springer-Verlag, 1996, pp. 392–399.
Smyth, B. and Keane, M.: Adaptation-Guided Retrieval: Questioning the Similarity Assumption in Reasoning, Artificial Intelligence 102 (1998), 249–293.
Watson, I. (ed.): Applying Case-Based Reasoning: Techniques for Enterprise Systems, Morgan Kaufmann, 1997.
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McGinty, L., Smyth, B. (2000). Personalised Route Planning: A Case-Based Approach. In: Blanzieri, E., Portinale, L. (eds) Advances in Case-Based Reasoning. EWCBR 2000. Lecture Notes in Computer Science, vol 1898. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44527-7_37
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DOI: https://doi.org/10.1007/3-540-44527-7_37
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