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Mixed-initiative problem solving with decision trees

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Abstract

We present a mixed-initiative approach to problem solving based on decision trees in which the user can answer unknown to any question she is asked by the intelligent system, or answer questions anywhere in the decision tree without waiting to be asked. Also in contrast to the traditional decision-tree approach, more than one of the rules in a decision tree may contribute to the solution of a problem for which the user is unable to provide a complete description. As shown by our results, increased coverage of incomplete problem descriptions is an important benefit for some decision trees. However, a potential risk in allowing a problem-solving dialogue to continue when relevant test results are not available is that no solution may be possible no matter what additional information the user can provide. This problem is addressed in our approach by using meta-level reasoning to recognize when no solution is possible.

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References

  • Aha DW, Breslow L, Muñoz-Avila H (2001) Conversational case-based reasoning. Appl Intell 14: 9–32

    Article  MATH  Google Scholar 

  • Aha DW, McSherry D, Yang Q (2005) Advances in conversational case-based reasoning. Knowl Eng Rev 20: 247–254

    Article  Google Scholar 

  • Allen JE (1999) Mixed-initiative interaction. IEEE Intell Syst 6: 14–16

    Article  Google Scholar 

  • Asuncion A, Newman DJ (2007) UCI machine learning repository. University of California, Department of Information and Computer Science, Irvine, California. http://www.ics.uci.edu/~mlearn/MLRepository.html

  • Bergmann R, Cunningham P (2002) Acquiring customers’ requirements in electronic commerce. Artif Intell Rev 18: 63–193

    Article  Google Scholar 

  • Cendrowska J (1987) PRISM: an algorithm for inducing modular rules. Int J Man-Machine Stud 27: 349–370

    Article  MATH  Google Scholar 

  • Cheetham W (2005) A mixed-initiative call center application for appliance diagnostics. In: Aha DW, Tecuci G (eds) Proceedings of the AAAI-05 fall symposium on mixed-initiative problem-solving assistants. AAAI/MIT Press

  • Cox M (2005) Metacognition in computation: a selected research review. Artif Intell 169: 104–141

    Article  Google Scholar 

  • Göker MH (2003) Adapting to the level of experience of the user in mixed-initiative web self-service applications. ICCBR-03 workshop on mixed-initiative case-based reasoning

  • Lenat D, Davis R, Doyle J, Genesereth M, Goldstein I, Schrobe H (1983) Reasoning about reasoning. In: Hayes-Roth F, Waterman D, Lenat D (eds) Building expert systems. Addison-Wesley, Reading

    Google Scholar 

  • McLaren B, Ashley K (2001) Helping a CBR program to know what it knows. In: Aha DW, Watson I (eds) Case-based reasoning research and development. LNAI, vol 2080. Springer, Berlin, pp 377–391

    Chapter  Google Scholar 

  • McSherry D (1999) Strategic induction of decision trees. Knowl Based Syst 12: 269–275

    Article  Google Scholar 

  • McSherry D (2001) Interactive case-based reasoning in sequential diagnosis. Appl Intell 14: 65–76

    Article  MATH  Google Scholar 

  • McSherry D (2003) Mixed-initiative intelligent systems for classification and diagnosis. In: Proceedings of the 14th Irish conference on artificial intelligence and cognitive science, pp 146–151

  • Quinlan JR (1986) Induction of decision trees. Mach Learn 1: 81–106

    Google Scholar 

  • Shimazu H, Shibata A, Nihei K (2001) ExpertGuide: a conversational case-based reasoning tool for developing mentors in knowledge spaces. Appl Intell 14: 33–48

    Article  MATH  Google Scholar 

  • Thompson CA, Göker MH, Langley P (2004) A personalized system for conversational recommendations. J Artif Intell Res 21: 393–428

    Google Scholar 

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Correspondence to David McSherry.

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McSherry, D. Mixed-initiative problem solving with decision trees. Artif Intell Rev 28, 17–33 (2007). https://doi.org/10.1007/s10462-008-9079-0

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