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Applications of logic under uncertainty
Probabilistic logic (also probability logic and probabilistic reasoning) involves the use of probability and logic to deal with uncertain situations. Probabilistic
Probabilistic_logic
Programming paradigm
Probabilistic logic programming is a programming paradigm that combines logic programming with probabilities. Most approaches to probabilistic logic programming
Probabilistic logic programming
Probabilistic_logic_programming
Learning logic programs from data
ACE) ProGolem Probabilistic inductive logic programming adapts the setting of inductive logic programming to learning probabilistic logic programs. It
Inductive_logic_programming
Probabilistic Soft Logic (PSL) is a statistical relational learning (SRL) framework for modeling probabilistic and relational domains. It is applicable
Probabilistic_soft_logic
Project for an open source artificial intelligence framework
inference and chaining. An implementation of a probabilistic reasoning engine based on probabilistic logic networks. The current implementation uses the
OpenCog
Probabilistic logic
A Markov logic network (MLN) is a probabilistic logic which applies the ideas of a Markov network to first-order logic, defining probability distributions
Markov_logic_network
Probabilistic logic programming language
probabilistic logic programming language that extends Prolog with probabilities. It minimally extends Prolog by adding the notion of a probabilistic fact
ProbLog
Software system for statistical models
Probabilistic logic programming is a programming paradigm that extends logic programming with probabilities. Most approaches to probabilistic logic programming
Probabilistic_programming
Probabilistic argumentation refers to different formal frameworks pertaining to probabilistic logic. All share the idea that qualitative aspects can be
Probabilistic_argumentation
Software able to infer logical consequences
There are also examples of probabilistic reasoners, including non-axiomatic reasoning systems, and probabilistic logic networks. Notable semantic reasoners
Semantic_reasoner
Indian-American computer scientist
Advancement of Artificial Intelligence (AAAI) for contributions to probabilistic database, logic programming, and intelligent agent-based systems. In 2022, Subrahmanian
V._S._Subrahmanian
Logical connective AND
logical equivalences First-order logic – Type of logical system Fréchet inequalities – Rules in probabilistic logic Homogeneity (linguistics) – Semantic
Logical_conjunction
Data having only values "true" or "false"
case of a more general logical data type—logic does not always need to be Boolean (see probabilistic logic). In programming languages with a built-in
Boolean_data_type
Inference seeking the simplest and most likely explanation
most likely hypothesis that should be adopted. Subjective logic generalises probabilistic logic by including degrees of epistemic uncertainty in the input
Abductive_reasoning
Data structure for Boolean functions
more succinct than OBDDs. SDDs are used as a compilation target for probabilistic logic programs by the ProbLog 2 system since they support tractable (weighted)
Sentential_decision_diagram
Subfield of artificial intelligence
uncertainty, these systems are normally based on fuzzy and non-classical logics or probabilistic methods made differentiable for use within neural networks. Neuro-symbolic
Neuro-symbolic_AI
Algebraic manipulation of "true" and "false"
logical truth values yields a multi-valued logic, which forms the basis for fuzzy logic and probabilistic logic. In these interpretations, a value is interpreted
Boolean_algebra
Type of probabilistic logic
Subjective logic is a type of probabilistic logic that explicitly takes epistemic uncertainty and source trust into account. In general, subjective logic is suitable
Subjective_logic
Model of logic based on matrix algebra
many-valued logic can be projected on scalar functions and generate a particular class of probabilistic logic with similarities with the many-valued logic of Reichenbach
Vector_logic
Topics referred to by the same term
have affinity for various antigens Polyvalent logic, a form of many-valued logic or probabilistic logic Polyvalent vaccine, a vaccine that can vaccinate
Polyvalence
Written work by John Maynard Keynes
classic account of the logical interpretation of probability (or probabilistic logic), a view of probability that has been continued by such later works
A_Treatise_on_Probability
Subdiscipline of artificial intelligence
first-order logic to describe relational properties of a domain in a general manner (universal quantification) and draw upon probabilistic graphical models
Statistical relational learning
Statistical_relational_learning
Topics referred to by the same term
non-constructive existence proof in mathematics Probabilistic argumentation in formal frameworks pertaining to probabilistic logic This disambiguation page lists articles
Probabilistic_argument
to be verified against these models are expressed in probabilistic extensions of temporal logic, such as PCTL. PRISM's companion tool PRISM-games provides
PRISM_model_checker
Probabilistic Computation Tree Logic (PCTL) is an extension of computation tree logic (CTL) that allows for probabilistic quantification of described
Probabilistic_CTL
Form of reasoning
logical argument that applies deductive reasoning Subjective logic – Type of probabilistic logic Theory of justification – Concept in epistemologyPages displaying
Deductive_reasoning
Branch of mathematics concerning probability
statistics to predict outcomes Probabilistic logic – Applications of logic under uncertainty Probabilistic proofs of non-probabilistic theorems Probability distribution –
Probability_theory
Intelligence in machines
action (it is not "deterministic"). It must choose an action by making a probabilistic guess and then reassess the situation to see if the action had the desired
Artificial_intelligence
Study of correct reasoning
Logic is the study of correct reasoning. It includes both formal and informal logic. Formal logic is the study of deductively valid inferences or logical
Logic
Methods in artificial intelligence research
first-order logic, e.g., with either Markov Logic Networks or Probabilistic Soft Logic. Other, non-probabilistic extensions to first-order logic to support
Symbolic artificial intelligence
Symbolic_artificial_intelligence
Closed interval [0,1] on the real number line
logical truth values yields a multi-valued logic, which forms the basis for fuzzy logic and probabilistic logic. In these interpretations, a value is interpreted
Unit_interval
Algorithm that employs a degree of randomness as part of its logic or procedure
algorithm is an algorithm that employs a degree of randomness as part of its logic or procedure. The algorithm typically uses uniformly random bits as an auxiliary
Randomized_algorithm
American computer scientist and AI researcher
Artificial General Intelligence. Springer. Ben Goertzel (2006). Probabilistic Logic Networks: A Comprehensive Framework for Uncertain Inference. Plenum
Ben_Goertzel
Programming paradigm based on formal logic
combining logic programming, learning and probability, has given rise to the fields of statistical relational learning and probabilistic inductive logic programming
Logic_programming
Logical problem studied in computer science
In computer science and mathematical logic, satisfiability modulo theories (SMT) is the problem of determining whether a mathematical formula is satisfiable
Satisfiability modulo theories
Satisfiability_modulo_theories
Probabilistic graphical model
to probabilistic Boolean networks and can, similarly, be used to model dynamical systems at steady-state. Recursive Bayesian estimation Probabilistic logic
Dynamic_Bayesian_network
Reasoning of knowledge about knowledge
(completely certain, that is, known). In probabilistic logic networks, truth values are also given a probabilistic interpretation: truth values may be uncertain
Autoepistemic_logic
Topics referred to by the same term
intelligence agency Dempster–Shafer theory, in probabilistic logic, a model of uncertainty Descriptive set theory, in logic Discrete sine transform, a Fourier transform
DST_(disambiguation)
Branch of statistics
squares regression Pathogenesis Pathology Probabilistic causation Probabilistic argumentation Probabilistic logic Regression analysis Transfer entropy Pearl
Causal_inference
Mathematical framework to model epistemic uncertainty
optimizing robustness to failure Subjective logic – Type of probabilistic logic Doxastic logic – Type of logic regarding reasoning about beliefs Linear belief
Dempster–Shafer_theory
Method of deriving conclusions
Some many-valued logics take the form of probability logics, which make it possible to reason from uncertain information to probabilistic conclusions. Various
Rule_of_inference
Topics referred to by the same term
the orchid genus Pleione .pln, a file extension used by SilkTest Probabilistic logic network Planetary nebula Polish złoty, currency by ISO 4217 currency
PLN
Combinational digital circuit
In computing, an arithmetic logic unit (ALU) is a combinational digital circuit that performs arithmetic and bitwise operations on integer binary numbers
Arithmetic_logic_unit
Rules in probabilistic logic
In probabilistic logic, the Fréchet inequalities, also known as the Boole–Fréchet inequalities, are rules implicit in the work of George Boole and explicitly
Fréchet_inequalities
Syllogism with conditional premise(s)
including, for example, non-monotonic logic, probabilistic logic and default logic. The reason for this is that these logics describe defeasible reasoning, and
Hypothetical_syllogism
Concept in mathematical logic
logical truth values yields a multi-valued logic, which forms the basis for fuzzy logic and probabilistic logic. In these interpretations, a value is interpreted
Boolean_domain
Study of the semantics, or interpretations, of formal and natural languages
logics of (finite) partially ordered quantification, which were originally investigated by Leon Henkin, who studied Henkin quantifiers. Probabilistic
Semantics_(logic)
(natural language processing, speech recognition, machine vision, probabilistic logic, planning, reasoning, many forms of machine learning) into an AI
List of artificial intelligence projects
List_of_artificial_intelligence_projects
Pattern matching algorithm
already implements the Rete algorithm) to make it support probabilistic logic, like fuzzy logic and Bayesian networks. Action selection mechanism Inference
Rete_algorithm
Topics referred to by the same term
Tramway Pop-up satellite archival tag The problem of Probabilistic Satisfiability in Probabilistic logic ParkinsonSAT, a technology demonstration and amateur
PSAT
Basic circuit in quantum computing
computation, a quantum logic gate (or simply quantum gate) is a basic quantum circuit operating on a small number of qubits. Quantum logic gates are the building
Quantum_logic_gate
Fuzzy logic concept
operation used in the framework of probabilistic metric spaces and in multi-valued logic, specifically in fuzzy logic. A t-norm generalizes intersection
T-norm
Process of identifying causality
knowing what caused the stick to move. Probabilistic causation Probabilistic argumentation Probabilistic logic Falcon, Andrea (2015-01-01). "Aristotle
Causal_reasoning
Overview of and topical guide to computer programming
functional Logic Abductive logic Answer set Concurrent logic Functional logic Inductive logic Probabilistic logic Event-driven Time-driven Expression-oriented Feature-oriented
Outline of computer programming
Outline_of_computer_programming
Knowledge Engine (Wikimedia Foundation) Question answering Probabilistic logic Probabilistic logic network Dempster–Shafer theory "Avoin tiede:tietokide –
Knowledge_crystal
Family of logics for natural-language and counterfactual conditionals
update/imaging. Beyond topic relevance in relevance logic, many theorists require that A make a (probabilistic or doxastic) difference to B for a conditional
Conditional_logic
Reasoning for mathematical statements
frequently used as an assumption for further mathematical work. Proofs employ logic expressed in mathematical symbols, along with natural language that usually
Mathematical_proof
Relationship in which one statement follows from another
Peirce's law Probabilistic logic Propositional calculus Sole sufficient operator Strawson entailment Strict conditional Tautology (logic) Tautological
Logical_consequence
Number measuring the chance an event occurs
appearance of subjectively probabilistic experimental outcomes. Mathematics portal Philosophy portal Contingency Equiprobability Fuzzy logic Heuristic (psychology)
Probability
Representations of imprecise probability
_{p\in C}p(A)} The upper and lower probabilities also relate to probabilistic logic: see Gerla (1994). Observe also that a necessity measure can be seen
Upper_and_lower_probabilities
Language for reasoning and representing events
Epistemic Probabilistic Event Calculus (EPEC) Notable extensions of the event calculus include Markov logic networks–based variants probabilistic, epistemic
Event_calculus
Mathematical theory for handling uncertainty
example Gerla 2001). Fuzzy measure theory Logical possibility Modal logic Probabilistic logic Random-fuzzy variable Transferable belief model Upper and lower
Possibility_theory
Statistics concept
but an inference engine to automate probabilistic reasoning—a kind of Prolog for probability instead of logic. Bayesian programming is a formal and
Bayesian_programming
Topics referred to by the same term
refer to: Probabilistic logic, a combination of the capacity of probability theory to handle uncertainty with the capacity of deductive logic to exploit
Evidential_reasoning
Philosophical concept
reasonings concerning matters of fact is not classical logic, but rather some kind of probabilistic logic where we associate a probability to factual statements
The_Missing_Shade_of_Blue
Evidence that either supports or counters a scientific theory
endeavour to gain knowledge Probabilistic causation Probabilistic argumentation Probabilistic logic – Applications of logic under uncertainty Opinion –
Scientific_evidence
German philosopher (1891–1953)
theory of probability; the logic and the philosophy of mathematics; space, time, and relativity theory; analysis of probabilistic reasoning; and quantum mechanics
Hans_Reichenbach
Natural-language "if" sentences about what may be the case
proposals include truth-functional analyses, pragmatics-augmented accounts, probabilistic ("suppositional") approaches, possible-worlds semantics, and restrictor
Indicative_conditional
themes. Joint scientific and technological cooperation in ML, and probabilistic logic techniques for various data types and combinations were added to
Artificial intelligence in India
Artificial_intelligence_in_India
Area of automatic programming
such as functional logic programming, constraint programming, probabilistic programming, abductive logic programming, modal logic, action languages, agent
Inductive_programming
Argument that uses faulty reasoning
the content rather than the form of the argument. An example is a probabilistically valid instance of the formally invalid argument form of denying the
Fallacy
Concept of philosophy and logic used to express modal claims
used as a formal device in logic, philosophy, and linguistics in order to provide a semantics for intensional and modal logic. Their metaphysical status
Possible_world
norm based mathematical fuzzy logic. In E.P. Klement & R. Mesiar (eds.), Logical, Algebraic, Analytic and Probabilistic Aspects of Triangular Norms, pp
T-norm_fuzzy_logics
Bearer of truth values
Similarly, deterministic propositions express certain information, while probabilistic propositions indicate degrees of uncertainty. Normative propositions
Proposition
Computing using random bit streams
ergodic processing. Unconventional computing von Neumann, J. (1963). "Probabilistic logics and the synthesis of reliable organisms from unreliable components"
Stochastic_computing
machines. Fuzzy logic Probabilistic logic Plausible reasoning Imprecise probability C. J. van Rijsbergen (1986), A non-classical logic for information
Uncertain_inference
Steps in reasoning
demonstrated by the Wason selection task. Another example, involving probabilistic reasoning, is the conjunction fallacy, where people judge a conjunction
Inference
Problem in network theory
probability distribution over the unobserved links. Probabilistic soft logic (PSL) is a probabilistic graphical model over hinge-loss Markov random field
Link_prediction
Form of incorrect argument in natural language
outcome. But even if every step in this chain is relatively probable, probabilistic calculus may still reveal that the likelihood of all steps occurring
Informal_fallacy
Computer science field
a task in logic, namely to check whether a structure satisfies a given logical formula. This general concept applies to many kinds of logic and many kinds
Model_checking
Theory in computer science
order to take advantage of the QBF solvers. Probabilistic CTL Fair computational tree logic Linear temporal logic Vardi, Moshe Y. (2001). Branching vs. Linear
Computation_tree_logic
Interdisciplinary study of systems
Cerebral Mechanisms in Behavior. pp. 1–41. von Neumann, John (1956). "Probabilistic Logics and the Synthesis of Reliable Organisms from Unreliable Components"
Systems_theory
Method of logical reasoning
definite probabilistic characterisation of each of them (in terms of likelihoods) and precise prior probabilities for them (e.g. based on logic or induction
Inductive_reasoning
Process of drawing correct inferences
would find convincing. The main discipline studying logical reasoning is logic. Distinct types of logical reasoning differ from each other concerning the
Logical_reasoning
vision) Powered exoskeleton Principle of rationality Probabilistic logic network Probabilistic roadmap PROGOL Programmable Universal Machine for Assembly
Index_of_robotics_articles
Look up Appendix:Glossary of logic in Wiktionary, the free dictionary. This is a glossary of logic. Logic is the study of the principles of valid reasoning
Glossary_of_logic
German computer scientist
(2008) Probabilistic Inductive Logic Programming. In: De Raedt L., Frasconi P., Kersting K., Muggleton S. (eds) Probabilistic Inductive Logic Programming
Kristian_Kersting
Natural-language understanding software
To this end, PRAC maintains probabilistic first-order knowledge bases over semantic networks represented in Markov logic networks. As opposed to other
Probabilistic_Action_Cores
June–July 1949 in Los Angeles, Summary written by G. E. Forsynthe. 1956. Probabilistic Logics and the Synthesis of Reliable Organisms from Unreliable Components
List of scientific publications by John von Neumann
List_of_scientific_publications_by_John_von_Neumann
1982 book by Jeremy Campbell
use ordinary, formal logic, which deals with events that definitely will happen or definitely will not happen. A probabilistic logic is needed, one that
Grammatical_Man
Mathematical method of risk analysis
on the expression. A similar problem one presents in the case of probabilistic logic (see for example Gerla 1994). If the probabilities of the events
Probability_bounds_analysis
British social scientist
through sequences of events, blending case-based reasoning with probabilistic logic. His 2009 paper “A Case for Cases” and later work explore how such
Peter_Abell
Resilience of systems to component failures or errors
Fault-Tolerant Computing (FTSC-15), pp. 2–11. von Neumann, J. (1956). "Probabilistic Logics and Synthesis of Reliable Organisms from Unreliable Components",
Fault_tolerance
probabilists Nuisance variable Probabilistic encryption Probabilistic logic Probabilistic proofs of non-probabilistic theorems Pseudocount "Core": 455
Catalog of articles in probability theory
Catalog_of_articles_in_probability_theory
Concept in computer science
computer science, bounded-error probabilistic polynomial time (BPP) is the class of decision problems solvable by a probabilistic Turing machine in polynomial
BPP_(complexity)
British professor
structured and probabilistic knowledge. She has been awarded the prize for the best application paper at the International Conference on Logic Programming
Alessandra_Russo
Task of finding records in a data set that refer to same entity across different sources
American Journal of Public Health. Howard B. Newcombe then laid the probabilistic foundations of modern record linkage theory in a 1959 article in Science
Record_linkage
Computer system simulating intelligence
is based on the model of the human brain with probabilistic thinking, fuzzy logic and multi-valued logic. Soft computing can process a wealth of data and
Computational_intelligence
Concept in computer science
computational processes that are nondeterministic (in the sense of being probabilistic or random), the relation between old and new states is not a single-valued
Reversible_computing
Logic programming using abductive reasoning
Abductive logic programming (ALP) is a high-level knowledge-representation framework that can be used to solve problems declaratively, based on abductive
Abductive_logic_programming
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