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Probabilistic logic and probabilistic networks
, 2008
"... While in principle probabilistic logics might be applied to solve a range of problems, in practice they are rarely applied at present. This is perhaps because they seem disparate, complicated, and computationally intractable. However, we shall argue in this programmatic paper that several approaches ..."
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Cited by 19 (15 self)
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While in principle probabilistic logics might be applied to solve a range of problems, in practice they are rarely applied at present. This is perhaps because they seem disparate, complicated, and computationally intractable. However, we shall argue in this programmatic paper that several approaches to probabilistic logic fit into a simple unifying framework: logically complex evidence can be used to associate probability intervals or probabilities with sentences. Specifically, we show in Part I that there is a natural way to present a question posed in probabilistic logic, and that various inferential procedures provide semantics for that question: the standard probabilistic semantics (which takes probability functions as models), probabilistic argumentation (which considers the probability of a hypothesis being a logical consequence of the available evidence), evidential probability (which handles reference classes and frequency data), classical statistical inference
Two puzzles concerning measures of uncertainty and the positive Boolean connectives
 Progress in Artificial Intelligence, 13th Portuguese Conference on Artificial Intelligence, LNAI 4874
, 2007
"... Abstract. The two puzzles are the Lottery Paradox and the Amalgamation Paradox, which both point out difficulties for aggregating uncertain information. A generalization of the lottery paradox is presented and a new form of an amalgamation reversal is introduced. Together these puzzles highlight a d ..."
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Cited by 5 (4 self)
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Abstract. The two puzzles are the Lottery Paradox and the Amalgamation Paradox, which both point out difficulties for aggregating uncertain information. A generalization of the lottery paradox is presented and a new form of an amalgamation reversal is introduced. Together these puzzles highlight a difficulty for introducing measures of uncertainty to a variety of logical knowledge representation frameworks. The point is illustrated by contrasting the constraints on solutions to each puzzle with the structural properties of the preferential semantics for nonmonotonic logics (System P), and also with systems of normal modal logics. The difficulties illustrate several points of tensions between the aggregation of uncertain information and aggregation according to the monotonically positive Boolean connectives, ∧ and ∨. 1
Evidential probability and objective Bayesian epistemology
 Handbook of the Philosophy of Statistics
, 2009
"... In this chapter we draw connections between two seemingly opposing approaches to probability and statistics: evidential probability on the one hand and objective Bayesian epistemology on the other. ..."
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Cited by 3 (3 self)
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In this chapter we draw connections between two seemingly opposing approaches to probability and statistics: evidential probability on the one hand and objective Bayesian epistemology on the other.
NO revision and NO contraction
"... Abstract. One goal of normative multiagent system theory is to formulate principles for normative system change that maintain the rulelike structure of norms and preserve links between norms and individual agent obligations. A central question raised by this problem is whether there is a framework ..."
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Cited by 3 (0 self)
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Abstract. One goal of normative multiagent system theory is to formulate principles for normative system change that maintain the rulelike structure of norms and preserve links between norms and individual agent obligations. A central question raised by this problem is whether there is a framework for norm change that is at once specific enough to capture this rulelike behavior of norms, yet general enough to support a full battery of norm and obligation change operators. In this paper we propose an answer to this question by developing a bimodal logic for norms and obligations called NO. A key point of our approach is that norms are treated as propositional formulas, and we provide some independent reasons for adopting this stance. Then we define norm change operations for a wide class of modal systems, including the class of NO systems, by constructing a class of modal revision operators that satisfy all the AGM postulates for revision, and constructing a class of modal contraction operators that satisfy all the AGM postulates for contraction. 1
Applied Logic without Psychologism
"... Abstract. Logic is a celebrated representation language because of its formal generality. But there are two senses in which a logic may be considered general, one that concerns a technical ability to discriminate between different types of individuals, and another that concerns constitutive norms fo ..."
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Cited by 2 (0 self)
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Abstract. Logic is a celebrated representation language because of its formal generality. But there are two senses in which a logic may be considered general, one that concerns a technical ability to discriminate between different types of individuals, and another that concerns constitutive norms for reasoning as such. This essay embraces the former, permutationinvariance conception of logic and rejects the latter, Fregean conception of logic. The question of how to apply logic under this pure invariantist view is addressed, and a methodology is given. The pure invariantist view is contrasted with logical pluralism, and a methodology for applied logic is demonstrated in remarks on a variety of issues concerning nonmonotonic logic and nonmonotonic inference, including Charles Morgan’s impossibility results for nonmonotonic logic, David Makinson’s normative constraints for nonmonotonic inference, and Igor Douven and Timothy Williamson’s proposed formal constraints on rational acceptance. 1
EVIDENTIAL PROBABILITY, OBJECTIVE BAYESIANISM, NONMONOTONICITY AND SYSTEM P
"... Abstract: This paper is a comparison of how firstorder Kyburgian Evidential Probability (EP), secondorder EP, and objective Bayesian epistemology compare as to the KLM systemP rules for consequence relations and the monotonic / nonmonotonic divide. 1 ..."
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Cited by 1 (1 self)
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Abstract: This paper is a comparison of how firstorder Kyburgian Evidential Probability (EP), secondorder EP, and objective Bayesian epistemology compare as to the KLM systemP rules for consequence relations and the monotonic / nonmonotonic divide. 1
2.2 Calculating Evidential Probability................. 7
, 2009
"... In this chapter we draw connections between two seemingly opposing approaches to probability and statistics: evidential probability on the one hand and objective Bayesian epistemology on the other. ..."
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In this chapter we draw connections between two seemingly opposing approaches to probability and statistics: evidential probability on the one hand and objective Bayesian epistemology on the other.
Gregory Wheeler Applied Logic without
"... Abstract. Logic is a celebrated representation language because of its formal generality. But there are two senses in which a logic may be considered general, one that concerns a technical ability to discriminate between different types of individuals, and another that concerns constitutive norms fo ..."
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Abstract. Logic is a celebrated representation language because of its formal generality. But there are two senses in which a logic may be considered general, one that concerns a technical ability to discriminate between different types of individuals, and another that concerns constitutive norms for reasoning as such. This essay embraces the former, permutationinvariance conception of logic and rejects the latter, Fregean conception of logic. The question of how to apply logic under this pure invariantist view is addressed, and a methodology is given. The pure invariantist view is contrasted with logical pluralism, and a methodology for applied logic is demonstrated in remarks on a variety of issues concerning nonmonotonic logic and nonmonotonic inference, including Charles Morgan’s impossibility results for nonmonotonic logic, David Makinson’s normative constraints for nonmonotonic inference, and Igor Douven and Timothy Williamson’s proposed formal constraints on rational acceptance.
Modeling of Phenomena and Dynamic Logic of Phenomena
, 2011
"... a complex of Computer phenomenon Science such as the mind presents tremendous computational complexity>> The New University of Lisbon, FCT challenges. Modeling field theory (MFT) addresses these challenges in a nontraditional way. The main idea behind MFT is to match levels of uncertainty of the mo ..."
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a complex of Computer phenomenon Science such as the mind presents tremendous computational complexity>> The New University of Lisbon, FCT challenges. Modeling field theory (MFT) addresses these challenges in a nontraditional way. The main idea behind MFT is to match levels of uncertainty of the model (also, a problem or some theory) with levels of uncertainty of the evaluation criterion used to identify that model. When a model becomes more certain, then the evaluation criterion is adjusted dynamically to match that change to the model. This process is called the Dynamic Logic of Phenomena (DLP) for model construction and it mimics processes of the mind and natural evolution. This paper provides a formal description of DLP by specifying its syntax, semantics, and reasoning system. We also outline links between DLP and other logical approaches. Computational complexity issues that motivate this work are presented using an example of polynomial models. I.