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Fluent (artificial Intelligence)
In artificial intelligence, a fluent is a condition that can change over time. In logical approaches to reasoning about actions, fluents can be represented in first-order logic by predicates having an argument that depends on time. For example, the condition "the box is on the table", if it can change over time, cannot be represented by \mathrm(\mathrm,\mathrm); a third argument is necessary to the predicate \mathrm to specify the time: \mathrm(\mathrm,\mathrm,t) means that the box is on the table at time t. This representation of fluents is modified in the situation calculus by using the sequence of the past actions in place of the current time. A fluent can also be represented by a function, dropping the time argument. For example, that the box is on the table can be represented by on(box,table), where on is a function and not a predicate. In first order logic, converting predicates to functions is called reification; for this reason, fluents represented by functions are said ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial Intelligence
Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech recognition, computer vision, translation between (natural) languages, as well as other mappings of inputs. The ''Oxford English Dictionary'' of Oxford University Press defines artificial intelligence as: the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. AI applications include advanced web search engines (e.g., Google), recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Tesla), automated decision-making and competing at the highest level in strategic game systems (such as chess and Go). ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Logic
Logic is the study of correct reasoning. It includes both formal and informal logic. Formal logic is the science of deductively valid inferences or of logical truths. It is a formal science investigating how conclusions follow from premises in a topic-neutral way. When used as a countable noun, the term "a logic" refers to a logical formal system that articulates a proof system. Formal logic contrasts with informal logic, which is associated with informal fallacies, critical thinking, and argumentation theory. While there is no general agreement on how formal and informal logic are to be distinguished, one prominent approach associates their difference with whether the studied arguments are expressed in formal or informal languages. Logic plays a central role in multiple fields, such as philosophy, mathematics, computer science, and linguistics. Logic studies arguments, which consist of a set of premises together with a conclusion. Premises and conclusions are usually un ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
First-order Logic
First-order logic—also known as predicate logic, quantificational logic, and first-order predicate calculus—is a collection of formal systems used in mathematics, philosophy, linguistics, and computer science. First-order logic uses quantified variables over non-logical objects, and allows the use of sentences that contain variables, so that rather than propositions such as "Socrates is a man", one can have expressions in the form "there exists x such that x is Socrates and x is a man", where "there exists''"'' is a quantifier, while ''x'' is a variable. This distinguishes it from propositional logic, which does not use quantifiers or relations; in this sense, propositional logic is the foundation of first-order logic. A theory about a topic is usually a first-order logic together with a specified domain of discourse (over which the quantified variables range), finitely many functions from that domain to itself, finitely many predicates defined on that domain, and a set of ax ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Predicate (logic)
In logic, a predicate is a symbol which represents a property or a relation. For instance, in the first order formula P(a), the symbol P is a predicate which applies to the individual constant a. Similarly, in the formula R(a,b), R is a predicate which applies to the individual constants a and b. In the semantics of logic, predicates are interpreted as relations. For instance, in a standard semantics for first-order logic, the formula R(a,b) would be true on an interpretation if the entities denoted by a and b stand in the relation denoted by R. Since predicates are non-logical symbols, they can denote different relations depending on the interpretation used to interpret them. While first-order logic only includes predicates which apply to individual constants, other logics may allow predicates which apply to other predicates. Predicates in different systems * In propositional logic, atomic formulas are sometimes regarded as zero-place predicates In a sense, these are nullar ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Situation Calculus
The situation calculus is a logic formalism designed for representing and reasoning about dynamical domains. It was first introduced by John McCarthy in 1963. The main version of the situational calculus that is presented in this article is based on that introduced by Ray Reiter in 1991. It is followed by sections about McCarthy's 1986 version and a logic programming formulation. Overview The situation calculus represents changing scenarios as a set of first-order logic formulae. The basic elements of the calculus are: *The actions that can be performed in the world *The fluents that describe the state of the world *The situations A domain is formalized by a number of formulae, namely: *Action precondition axioms, one for each action *Successor state axioms, one for each fluent *Axioms describing the world in various situations *The foundational axioms of the situation calculus A simple robot world will be modeled as a running example. In this world there is a single robot a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Reification (knowledge Representation)
Reification in knowledge representation is the process of turning a predicate or statement into an addressable object. Reification allows the representation of assertions so that they can be referred to or qualified by ''other'' assertions, i.e., meta-knowledge. The message "John is six feet tall" is an assertion involving truth that commits the speaker to its factuality, whereas the reified statement "Mary reports that John is six feet tall" defers such commitment to Mary. In this way, the statements can be incompatible without creating contradictions in reasoning. For example, the statements "John is six feet tall" and "John is five feet tall" are mutually exclusive (and thus incompatible), but the statements "Mary reports that John is six feet tall" and "Paul reports that John is five feet tall" are not incompatible, as they are both governed by a conclusive rationale that either Mary or Paul is (or both are), in fact, incorrect. In linguistics, reporting, telling, and saying a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Event Calculus
The event calculus is a logical language for representing and reasoning about events and their effects first presented by Robert Kowalski and Marek Sergot in 1986. It was extended by Murray Shanahan and Rob Miller in the 1990s. Similar to other languages for reasoning about change, the event calculus represents the effects of actions on fluents. However, events can also be external to the system. In the event calculus, one can specify the value of fluents at some given time points, the events that take place at given time points, and their effects. Fluents and events In the event calculus, fluents are reified. This means that they are not formalized by means of predicates but by means of functions. A separate predicate is used to tell which fluents hold at a given time point. For example, \mathit(on(box,table),t) means that the box is on the table at time ; in this formula, is a predicate while is a function. Events are also represented as terms. The effects of events are ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fluent Calculus
The fluent calculus is a formalism for expressing dynamical domains in first-order logic. It is a variant of the situation calculus; the main difference is that situations are considered representations of states. A binary function symbol \circ is used to concatenate the terms that represent facts that hold in a situation. For example, that the box is on the table in the situation s is represented by the formula \exists t . s = on(box,table) \circ t. The frame problem is solved by asserting that the situation after the execution of an action is identical to the one before but for the conditions changed by the action. For example, the action of moving the box from the table to the floor is formalized as: : State(Do(move(box,table,floor), s)) \circ on(box,table) = State(s) \circ on(box,floor) This formula states that the state after the move is added the term on(box,floor) and removed the term on(box,table). Axioms specifying that \circ is commutative and non-idempotent are necessary ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Features And Fluents Logic
Feature may refer to: Computing * Feature (CAD), could be a hole, pocket, or notch * Feature (computer vision), could be an edge, corner or blob * Feature (software design) is an intentional distinguishing characteristic of a software item (in performance, portability, or—especially—functionality) * Feature (machine learning), in statistics: individual measurable properties of the phenomena being observed Science and analysis * Feature data, in geographic information systems, comprise information about an entity with a geographic location * Features, in audio signal processing, an aim to capture specific aspects of audio signals in a numeric way * Feature (archaeology), any dug, built, or dumped evidence of human activity Media * Feature film, a film with a running time long enough to be considered the principal or sole film to fill a program ** Feature length, the standardized length of such films * Feature story, a piece of non-fiction writing about news * Radio doc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Event Calculus
The event calculus is a logical language for representing and reasoning about events and their effects first presented by Robert Kowalski and Marek Sergot in 1986. It was extended by Murray Shanahan and Rob Miller in the 1990s. Similar to other languages for reasoning about change, the event calculus represents the effects of actions on fluents. However, events can also be external to the system. In the event calculus, one can specify the value of fluents at some given time points, the events that take place at given time points, and their effects. Fluents and events In the event calculus, fluents are reified. This means that they are not formalized by means of predicates but by means of functions. A separate predicate is used to tell which fluents hold at a given time point. For example, \mathit(on(box,table),t) means that the box is on the table at time ; in this formula, is a predicate while is a function. Events are also represented as terms. The effects of events are ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fluent Calculus
The fluent calculus is a formalism for expressing dynamical domains in first-order logic. It is a variant of the situation calculus; the main difference is that situations are considered representations of states. A binary function symbol \circ is used to concatenate the terms that represent facts that hold in a situation. For example, that the box is on the table in the situation s is represented by the formula \exists t . s = on(box,table) \circ t. The frame problem is solved by asserting that the situation after the execution of an action is identical to the one before but for the conditions changed by the action. For example, the action of moving the box from the table to the floor is formalized as: : State(Do(move(box,table,floor), s)) \circ on(box,table) = State(s) \circ on(box,floor) This formula states that the state after the move is added the term on(box,floor) and removed the term on(box,table). Axioms specifying that \circ is commutative and non-idempotent are necessary ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Frame Problem
In artificial intelligence, the frame problem describes an issue with using first-order logic (FOL) to express facts about a robot in the world. Representing the state of a robot with traditional FOL requires the use of many axioms that simply imply that things in the environment do not change arbitrarily. For example, Hayes describes a "block world" with rules about stacking blocks together. In a FOL system, additional axioms are required to make inferences about the environment (for example, that a block cannot change position unless it is physically moved). The frame problem is the problem of finding adequate collections of axioms for a viable description of a robot environment. John McCarthy (computer scientist), John McCarthy and Patrick J. Hayes defined this problem in their 1969 article, ''Some Philosophical Problems from the Standpoint of Artificial Intelligence''. In this paper, and many that came after, the formal mathematical problem was a starting point for more general ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
