Plausibility Theory Edited by Gregory Wheeler (The New University of Lisbon)

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  1. Judea Pearl (1988). Probabilistic Reasoning in Intelligent Systems. Morgan Kaufmann.
    The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.
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  2. John R. Welch (2012). Real-Life Decisions and Decision Theory. In Sabine Roeser, Rafaela Hillerbrand, Per Sandin & Martin Peterson (eds.), Handbook of Risk Theory. Springer.
    Some decisions result in cognitive consequences such as information gained and information lost. The focus of this study, however, is decisions with consequences that are partly or completely noncognitive. These decisions are typically referred to as ‘real-life decisions’. According to a common complaint, the challenges of real-life decision making cannot be met by decision theory. This complaint has at least two principal motives. One is the maximizing objection that to require agents to determine the optimal act under real-world constraints is (...)
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  3. John R. Welch (2011). Decision Theory and Cognitive Choice. European Journal for Philosophy of Science 1 (2):147-172.
    The focus of this study is cognitive choice: the selection of one cognitive option (a hypothesis, a theory, or an axiom, for instance) rather than another. The study proposes that cognitive choice should be based on the plausibilities of states posited by rival cognitive options and the utilities of these options' information outcomes. The proposal introduces a form of decision theory that is novel because comparative; it permits many choices among cognitive options to be based on merely comparative plausibilities and (...)
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