Abstract
In Classical Decision Theory, preferences and uncertainties of a decision maker (DM) have the quantitative forms of a utility function and a probability distribution. However, a numerical approach for decision making suffers from a knowledge acquisition problem. In this paper a qualitative model for decision making is proposed, where the DM is modeled as the agent with preferences and beliefs about the world. Decision problem is represented by means of Brewka’s logic program with ordered disjunction (LPOD) and a decision making process is a constraint satisfaction problem, where a solution is consistent with a knowledge base and maximally consistent with the DM’s beliefs and preferences.
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Graboś, R. (2004). Qualitative Model of Decision Making. In: Bussler, C., Fensel, D. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2004. Lecture Notes in Computer Science(), vol 3192. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30106-6_49
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DOI: https://doi.org/10.1007/978-3-540-30106-6_49
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