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Towards autonomous decision-making: A probabilistic model for learning multi-user preferences

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  • Peters, M.
  • Ketter, W.

Abstract

Information systems have revolutionized the provisioning of decision-relevant information, and decision support tools have improved human decisions in many domains. Autonomous decision- making, on the other hand, remains hampered by systems’ inability to faithfully capture human preferences. We present a computational preference model that learns unobtrusively from lim- ited data by pooling observations across like-minded users. Our model quantifies the certainty of its own predictions as input to autonomous decision-making tasks, and it infers probabilistic segments based on user choices in the process. We evaluate our model on real-world preference data collected on a commercial crowdsourcing platform, and we find that it outperforms both individual and population-level estimates in terms of predictive accuracy and the informative- ness of its certainty estimates. Our work takes an important step toward systems that act autonomously on their users’ behalf.

Suggested Citation

  • Peters, M. & Ketter, W., 2013. "Towards autonomous decision-making: A probabilistic model for learning multi-user preferences," ERIM Report Series Research in Management ERS-2013-007-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  • Handle: RePEc:ems:eureri:40144
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    References listed on IDEAS

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    More about this item

    Keywords

    assistive technologies; autonomous decision-making; multi-task learning; preferences; software agents;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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