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Parallel Constraint Satisfaction Processes
Parallel constraint satisfaction processes (PCSP) is a model that integrates the fastest growing research areas in the study of the mind; Connectionism, neural networks, and parallel distributed processing models.Read, S.J., Vanman, E.J. & Miller L.C. (1997)Connectionism, parallel constraint satisfaction processes, and gestalt principles: (Re)Introducing cognitive dynamics to social psychology Personality and Social Psychology Review, 1 (1), 26–53. Dynamic model of attitude This model integrates these three areas to propose a holistic explanation for an individual's response to cognitive dissonance. It models an explanation of the dynamic structure of attitudes and the attitude change involved in cognitive dissonance theory. PCSP posits that beliefs impose constraints on other beliefs, and conditions can either constrain or make salient different aspects of one's beliefs. Attitudes and beliefs are therefore changeable, due to trying to satisfactorily fit with the various constrai ...
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Connectionism
Connectionism refers to both an approach in the field of cognitive science that hopes to explain mind, mental phenomena using artificial neural networks (ANN) and to a wide range of techniques and algorithms using ANNs in the context of artificial intelligence to build more intelligent machines. Connectionism presents a cognitive theory based on simultaneously occurring, distributed signal activity via connections that can be represented numerically, where learning occurs by modifying connection strengths based on experience. Some advantages of the connectionist approach include its applicability to a broad array of functions, structural approximation to biological neurons, low requirements for innate structure, and capacity for graceful degradation. Some disadvantages include the difficulty in deciphering how ANNs process information, or account for the compositionality of mental representations, and a resultant difficulty explaining phenomena at a higher level. The success of de ...
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Neural Networks
A neural network is a network or circuit of biological neurons, or, in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus, a neural network is either a biological neural network, made up of biological neurons, or an artificial neural network, used for solving artificial intelligence (AI) problems. The connections of the biological neuron are modeled in artificial neural networks as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed. This activity is referred to as a linear combination. Finally, an activation function controls the amplitude of the output. For example, an acceptable range of output is usually between 0 and 1, or it could be −1 and 1. These artificial networks may be used for predictive modeling, adaptive control and applications where they can be trained via a dataset. Self-learning resulting from ...
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Parallel Distributed Processing
Connectionism refers to both an approach in the field of cognitive science that hopes to explain mental phenomena using artificial neural networks (ANN) and to a wide range of techniques and algorithms using ANNs in the context of artificial intelligence to build more intelligent machines. Connectionism presents a cognitive theory based on simultaneously occurring, distributed signal activity via connections that can be represented numerically, where learning occurs by modifying connection strengths based on experience. Some advantages of the connectionist approach include its applicability to a broad array of functions, structural approximation to biological neurons, low requirements for innate structure, and capacity for graceful degradation. Some disadvantages include the difficulty in deciphering how ANNs process information, or account for the compositionality of mental representations, and a resultant difficulty explaining phenomena at a higher level. The success of deep ...
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Cognitive Dissonance
In the field of psychology, cognitive dissonance is the perception of contradictory information, and the mental toll of it. Relevant items of information include a person's actions, feelings, ideas, beliefs, values, and things in the environment. Cognitive dissonance is typically experienced as psychological stress when persons participate in an action that goes against one or more of those things. According to this theory, when two actions or ideas are not psychologically consistent with each other, people do all in their power to change them until they become consistent. The discomfort is triggered by the person's belief clashing with new information perceived, wherein the individual tries to find a way to resolve the contradiction to reduce their discomfort.Festinger, L. (1957). ''A Theory of Cognitive Dissonance''. California: Stanford University Press. In '' When Prophecy Fails: A Social and Psychological Study of a Modern Group That Predicted the Destruction of the World'' ...
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Attitude (psychology)
In psychology, attitude is a psychological construct that is a mental and emotional entity that inheres or characterizes a person, their attitude to approach to something, or their personal view on it. Attitude involves their mindset, outlook and feelings. Attitudes are complex and are an acquired state through life experience. Attitude is an individual's predisposed state of mind regarding a value and it is precipitated through a responsive expression towards oneself, a person, place, thing, or event (the attitude object) which in turn influences the individual's thought and action. Most simply understood attitudes in psychology are the feelings individuals have about themselves and the world. Prominent psychologist Gordon Allport described this latent psychological construct as "the most distinctive and indispensable concept in contemporary social psychology."Allport, Gordon. (1935). "Attitudes," in A Handbook of Social Psychology, ed. C. Murchison. Worcester, MA: Clark U ...
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Cognitive Dissonance Theory
In the field of psychology, cognitive dissonance is the perception of contradictory information, and the mental toll of it. Relevant items of information include a person's actions, feelings, ideas, beliefs, values, and things in the environment. Cognitive dissonance is typically experienced as psychological stress when persons participate in an action that goes against one or more of those things. According to this theory, when two actions or ideas are not psychologically consistent with each other, people do all in their power to change them until they become consistent. The discomfort is triggered by the person's belief clashing with new information perceived, wherein the individual tries to find a way to resolve the contradiction to reduce their discomfort.Festinger, L. (1957). ''A Theory of Cognitive Dissonance''. California: Stanford University Press. In '' When Prophecy Fails: A Social and Psychological Study of a Modern Group That Predicted the Destruction of the World'' ( ...
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Cognition
Cognition refers to "the mental action or process of acquiring knowledge and understanding through thought, experience, and the senses". It encompasses all aspects of intellectual functions and processes such as: perception, attention, thought, intelligence, the formation of knowledge, memory and working memory, judgment and evaluation, reasoning and computation, problem solving and decision making, comprehension and production of language. Imagination is also a cognitive process, it is considered as such because it involves thinking about possibilities. Cognitive processes use existing knowledge and discover new knowledge. Cognitive processes are analyzed from different perspectives within different contexts, notably in the fields of linguistics, musicology, anesthesia, neuroscience, psychiatry, psychology, education, philosophy, anthropology, biology, systemics, logic, and computer science. These and other approaches to the analysis of cognition (such as embodie ...
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Self
The self is an individual as the object of that individual’s own reflective consciousness. Since the ''self'' is a reference by a subject to the same subject, this reference is necessarily subjective. The sense of having a self—or ''selfhood''—should, however, not be confused with subjectivity itself. Ostensibly, this sense is directed outward from the subject to refer inward, back to its "self" (or itself). Examples of psychiatric conditions where such "sameness" may become broken include depersonalization, which sometimes occurs in schizophrenia: the self appears different from the subject. The first-person perspective distinguishes selfhood from personal identity. Whereas "identity" is (literally) sameness and may involve categorization and labeling, selfhood implies a first-person perspective and suggests potential uniqueness. Conversely, we use "person" as a third-person reference. Personal identity can be impaired in late-stage Alzheimer's disease and in other ne ...
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Social
Social organisms, including human(s), live collectively in interacting populations. This interaction is considered social whether they are aware of it or not, and whether the exchange is voluntary or not. Etymology The word "social" derives from the Latin word ''socii'' ("allies"). It is particularly derived from the Italian '' Socii'' states, historical allies of the Roman Republic (although they rebelled against Rome in the Social War of 91–87 BC). Social theorists In the view of Karl MarxMorrison, Ken. ''Marx, Durkheim, Weber. Formations of modern social thought'', human beings are intrinsically, necessarily and by definition social beings who, beyond being "gregarious creatures", cannot survive and meet their needs other than through social co-operation and association. Their social characteristics are therefore to a large extent an objectively given fact, stamped on them from birth and affirmed by socialization processes; and, according to Marx, in producing and reprodu ...
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Identity (social Science)
Identity is the qualities, beliefs, personality traits, appearance, and/or expressions that characterize a person or group.Compare ''Collins Dictionary of Sociology'', quoted in In sociology, emphasis is placed on collective identity, in which an individual's identity is strongly associated with role-behavior or the collection of group memberships that define them. According to Peter Burke, "Identities tell us who we are and they announce to others who we are." Identities subsequently guide behavior, leading "fathers" to behave like "fathers" and "nurses" to act like "nurses." In psychology, the term "identity" is most commonly used to describe personal identity, or the distinctive qualities or traits that make an individual unique. Identities are strongly associated with self-concept, self-image (one's mental model of oneself), self-esteem, and individuality. Individuals' identities are situated, but also contextual, situationally adaptive and changing. Despite their flu ...
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Gestalt Psychology
Gestalt-psychology, gestaltism, or configurationism is a school of psychology that emerged in the early twentieth century in Austria and Germany as a theory of perception that was a rejection of basic principles of Wilhelm Wundt's and Edward Titchener's elementalist and structuralist psychology.Mather, George (2006) Foundations of Perception, Psychology Pressch.1 p.32 As used in Gestalt psychology, the German word ''Gestalt'' ( , ; meaning "form") is interpreted as "pattern" or "configuration". Gestalt psychologists emphasize that organisms perceive entire patterns or configurations, not merely individual components. The view is sometimes summarized using the adage, "the whole is more than the sum of its parts." Gestalt psychology was founded on works by Max Wertheimer, Wolfgang Köhler, and Kurt Koffka. Origin and history Max Wertheimer (1880–1943), Kurt Koffka (1886–1941), and Wolfgang Köhler (1887-1967) founded Gestalt psychology in the early 20th century. ...
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Neural Network
A neural network is a network or neural circuit, circuit of biological neurons, or, in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus, a neural network is either a biological neural network, made up of biological neurons, or an artificial neural network, used for solving artificial intelligence (AI) problems. The connections of the biological neuron are modeled in artificial neural networks as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed. This activity is referred to as a linear combination. Finally, an activation function controls the amplitude of the output. For example, an acceptable range of output is usually between 0 and 1, or it could be −1 and 1. These artificial networks may be used for predictive modeling, adaptive control and applications where they can be trained via a dataset. Self-learning re ...
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