Common sense and maximum entropy
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Publication:1299784
DOI10.1023/A:1005081609010zbMath0931.68124MaRDI QIDQ1299784
Publication date: 2 November 1999
Published in: Synthese (Search for Journal in Brave)
Logic in artificial intelligence (68T27) Reasoning under uncertainty in the context of artificial intelligence (68T37) Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence (68T35) Measures of information, entropy (94A17)
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Robust reasoning with rules that have exceptions: From second-order probability to argumentation via upper envelopes of probability and possibility plus directed graphs ⋮ Objective Bayesianism and the maximum entropy principle ⋮ A foundational approach to generalising the maximum entropy inference process to the multi-agent context ⋮ Lakatos's criticism of Carnapian inductive logic was mistaken ⋮ A triple uniqueness of the maximum entropy approach ⋮ Deceptive updating and minimal information methods ⋮ Logical perspectives on the foundations of probability ⋮ Rules of proof for maximal entropy inference ⋮ Probabilism, entropies and strictly proper scoring rules ⋮ How uncertain do we need to be? ⋮ Determining maximal entropy functions for objective Bayesian inductive logic ⋮ The emergence of reasons conjecture. ⋮ Explaining default intuitions using maximum entropy. ⋮ ON FILLING-IN MISSING CONDITIONAL PROBABILITIES IN CAUSAL NETWORKS ⋮ Probabilistic knowledge representation using the principle of maximum entropy and Gröbner basis theory ⋮ Symmetry's end? ⋮ A representation theorem and applications to measure selection and noninformative priors ⋮ A note on irrelevance in inductive logic ⋮ The entropy-limit (conjecture) for \(\Sigma_2\)-premisses ⋮ Towards a Bayesian Theory of Second-Order Uncertainty: Lessons from Non-Standard Logics ⋮ Some observations on induction in predicate probabilistic reasoning
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