Non-classical logic | Probabilistic arguments

Probabilistic logic

Probabilistic logic (also probability logic and probabilistic reasoning) involves the use of probability and logic to deal with uncertain situations. Probabilistic logic extends traditional logic truth tables with probabilistic expressions. A difficulty of probabilistic logics is their tendency to multiply the computational complexities of their probabilistic and logical components. Other difficulties include the possibility of counter-intuitive results, such as in case of belief fusion in Dempster–Shafer theory. Source trust and epistemic uncertainty about the probabilities they provide, such as defined in subjective logic, are additional elements to consider. The need to deal with a broad variety of contexts and issues has led to many different proposals. (Wikipedia).

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Probabilistic logic programming and its applications - Luc De Raedt, Leuven

Probabilistic programs combine the power of programming languages with that of probabilistic graphical models. There has been a lot of progress in this paradigm over the past twenty years. This talk will introduce probabilistic logic programming languages, which are based on Sato's distrib

From playlist Logic and learning workshop

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Introduction to Predicate Logic

This video introduces predicate logic. mathispower4u.com

From playlist Symbolic Logic and Proofs (Discrete Math)

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Logic: The Structure of Reason

As a tool for characterizing rational thought, logic cuts across many philosophical disciplines and lies at the core of mathematics and computer science. Drawing on Aristotle’s Organon, Russell’s Principia Mathematica, and other central works, this program tracks the evolution of logic, be

From playlist Logic & Philosophy of Mathematics

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Probabilistic model 5: summary of assumptions

[http://bit.ly/BM-25] The summary of 7 assumptions made in the probabilistic model of IR, and why really need to make them. What assumptions can we relax?

From playlist Probabilistic Model of IR

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Introduction to Predicates and Quantifiers

This lesson is an introduction to predicates and quantifiers.

From playlist Mathematical Statements (Discrete Math)

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Introduction to Propositional Logic and Truth Tables

This video introduces propositional logic and truth tables. mathispower4u.com

From playlist Symbolic Logic and Proofs (Discrete Math)

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VALIDITY and ENTAILMENT in Truth Trees for Predicate Logic - Logic

In this video on Logic, we look at entailment and validity in truth trees for predicate logic. We learn how to do negated universal decomposition, negated existential decomposition, universal elimination, and existential elimination. We then do three practice truth trees. 0:00 - [Validity

From playlist Logic in Philosophy and Mathematics

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Translating ENGLISH into PREDICATE LOGIC - Logic

In this video on Logic, we learn to translate English sentences into Predicate Logic. We do sentences with only constants and predicates, as well as introduce the universal and existential quantifier "some x is P" and "every x is P" and then do some practice problems. Predicate Logic trans

From playlist Logic in Philosophy and Mathematics

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Richard Lassaigne: Introduction à la théorie de la complexité

Find this video and other talks given by worldwide mathematicians on CIRM's Audiovisual Mathematics Library: http://library.cirm-math.fr. And discover all its functionalities: - Chapter markers and keywords to watch the parts of your choice in the video - Videos enriched with abstracts, b

From playlist Mathematical Aspects of Computer Science

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Semantic models for higher-order Bayesian inference - Sam Staton, University of Oxford

In this talk I will discuss probabilistic programming as a method of Bayesian modelling and inference, with a focus on fully featured probabilistic programming languages with higher order functions, soft constraints, and continuous distributions. These languages are pushing the limits of e

From playlist Logic and learning workshop

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Hope for a Type-Theoretic Understanding of Zero-Knowledge - Noam Zeilberger

Noam Zeilberger IMDEA Software Institute; Member, School of Mathematics October 4, 2012 For more videos, visit http://video.ias.edu

From playlist Mathematics

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SEM122 - Predicate Logic I

This first E-Lecture on Predicate Logic is meant as a gentle introduction. It first points out why propositional logic alone is not sufficient for the formalization of sentence meaning and then introduces the central machinery of predicate logic using several examples with which the studen

From playlist VLC103 - The Nature of Meaning

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Integrating Inference with Stochastic Process Algebra Models - Jane Hillston, Edinburgh

ProPPA is a probabilistic programming language for continuous-time dynamical systems, developed as an extension of the stochastic process algebra Bio-PEPA. It offers a high-level syntax for describing systems of interacting components with stochastic behaviours where some of the parameters

From playlist Logic and learning workshop

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Classical and Quantum Subjectivity

Uncertainty is a major component of subjective logic beliefs. We discuss the cloud of uncertainty across Markov networks, insights from computational irreducibility, and negative quantum quasiprobabilities and beliefs.

From playlist Wolfram Technology Conference 2022

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Logic 3 - Propositional Logic Semantics | Stanford CS221: AI (Autumn 2021)

For more information about Stanford's Artificial Intelligence professional and graduate programs visit: https://stanford.io/ai Associate Professor Percy Liang Associate Professor of Computer Science and Statistics (courtesy) https://profiles.stanford.edu/percy-liang Assistant Professor

From playlist Stanford CS221: Artificial Intelligence: Principles and Techniques | Autumn 2021

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Marco Pavone: "On safe & efficient human-robot interactions via multimodal intent modeling & rea..."

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From playlist Mathematical Challenges and Opportunities for Autonomous Vehicles 2020

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Bayesian Inference by Program Verification - Joost-Pieter Katoen, RWTH Aachen University

In this talk, I will give a perspective on inference in Bayes' networks (BNs) using program verification. I will argue how weakest precondition reasoning a la Dijkstra can be used for exact inference (and more). As exact inference is NP-complete, inference is typically done by means of sim

From playlist Logic and learning workshop

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An Overview of Propositional Logic for Linguists - Semantics in Linguistics

This video covers propositional logic in #semantics for #linguistics. We talk about propositions, the negation, the conjunction, the conditional, the disjunction, truth tables, syntax of logic, tautologies, and contradictions all in 11 minutes. Join this channel to get access to perks: ht

From playlist Semantics in Linguistics

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Mini-course on information by Rajaram Nityananda (Part 2)

Information processing in biological systems URL: https://www.icts.res.in/discussion_meeting/ipbs2016/ DATES: Monday 04 Jan, 2016 - Thursday 07 Jan, 2016 VENUE: ICTS campus, Bangalore From the level of networks of genes and proteins to the embryonic and neural levels, information at var

From playlist Information processing in biological systems

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Statistical relational learning | Bayes' theorem | Truth value | Subjective logic | Probability space | Logic programming | Probability | Fréchet inequalities | Non-monotonic logic | Evidential reasoning approach | Logical consequence | Dempster–Shafer theory | Modus tollens | Cox's theorem | Possibility theory | Probabilistic soft logic | Imprecise probability | Logical disjunction | Atomic formula | Case-based reasoning | Posterior probability | Probabilistic argumentation | Uncertain inference | Probabilistic database | Truth table | Upper and lower probabilities | Markov chain | Bayesian probability | Modus ponens | Rudolf Carnap | Propositional variable | Σ-algebra | Dutch book | Probability theory | Logical conjunction | Fuzzy logic | Markov logic network | Bayesian inference