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Contributions to Deep Learning Models - RiuNet
Contributions to Deep Learning Models - RiuNet

... Deep Learning is a new area of Machine Learning research which aims to create computational models that learn several representations of the data using deep architectures. These methods have become very popular over the last few years due to the remarkable results obtained in speech recognition, vis ...
curriculum vitae - University of Memphis
curriculum vitae - University of Memphis

... representations: A study of how and why. Cognitive Psychology, 13, 1–26. Smith, D. A., & Graesser, A. C. (1981). Memory for actions in scripted activities as a function of typicality, retention interval, and retrieval task. Memory and Cognition, 9, 550–559. Woll, S. B., & Graesser, A. C. (1982). Mem ...
CURRICULUM VITAE - University of Memphis
CURRICULUM VITAE - University of Memphis

... representations: A study of how and why. Cognitive Psychology, 13, 1–26. Smith, D. A., & Graesser, A. C. (1981). Memory for actions in scripted activities as a function of typicality, retention interval, and retrieval task. Memory and Cognition, 9, 550–559. Woll, S. B., & Graesser, A. C. (1982). Mem ...
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as a PDF

... 6. Advanced GFS approaches 7. Conclusions. What’s next? ...
rtf - MIT Media Lab
rtf - MIT Media Lab

... project, we make use of this \u8220"functional\u8221" definition of concepts, where one event \u8220"concept\u8221" is the same as another if it is exchangeable within the event sequence.\par} {\pard \ql \f0 \sa0 \li720 \fi-360 \endash \tx360\tab {\b Induction} . The learning process of inferring th ...
querying description logic knowledge bases
querying description logic knowledge bases

... some part of the real world in a knowledge base, inferring new knowledge based on the given facts, and querying knowledge bases. The ability to infer new knowledge is one of the distinguishing features compared to databases. Such inference services require the definition of knowledge in a language f ...
uma modelagem dos processos cognitivo, emocional e motivacional
uma modelagem dos processos cognitivo, emocional e motivacional

... FCM system considering the interaction among the concepts. The results have shown quite coherence in relation to expected outcomes based on common sense experiences and in experts’ beliefs. The quality of them allows concluding that FCM tool is able to model psychological processes making possible i ...
Flexible Attention-based Cognitive Architecture for
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... engineering. Minsky has argued in his Society of Mind that intelligent behaviours can emerge from the interaction of many simple processes, even though each process may lack ‘intelligence’ in isolation. In addition, Anderson argued that an emergent system produces more complex behaviours and propert ...
Intelligence by Design - Department of Computer Science
Intelligence by Design - Department of Computer Science

... All intelligence relies on search — for example, the search for an intelligent agent’s next action. Search is only likely to succeed in resource-bounded agents if they have already been biased towards finding the right answer. In artificial agents, the primary source of bias is engineering. This dis ...
The Hidden Pattern
The Hidden Pattern

... with the demands of raising three children and repeatedly moving house -- not to mention getting divorced and remarried…. In short, modern human life in all its variety and chaos. Given all this, it’s been rather difficult for me to find time to work on this book. Every hour I’ve worked on this book ...
The DL-Lite Family - Dipartimento di Informatica e Sistemistica
The DL-Lite Family - Dipartimento di Informatica e Sistemistica

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Comparative Table of Cognitive Architectures (started
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An Opinionated History of AAAI - Association for the Advancement of
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Growth of the Internet (cont’d.)
Growth of the Internet (cont’d.)

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Monster Analogies - Semantic Scholar
Monster Analogies - Semantic Scholar

... ■ Analogy has a rich history in Western civilization. Over the centuries, it has become reified in that analogical reasoning has sometimes been regarded as a fundamental cognitive process. In addition, it has become identified with a particular expressive format. The limitations of the modern view a ...
Monster Analogies - Semantic Scholar
Monster Analogies - Semantic Scholar

... ■ Analogy has a rich history in Western civilization. Over the centuries, it has become reified in that analogical reasoning has sometimes been regarded as a fundamental cognitive process. In addition, it has become identified with a particular expressive format. The limitations of the modern view a ...
FS-FOIL: An Inductive Learning Method for Extracting Interpretable
FS-FOIL: An Inductive Learning Method for Extracting Interpretable

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Wrappers for feature subset selection
Wrappers for feature subset selection

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Humour - CSE, IIT Bombay
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cont`d. - PSY388
cont`d. - PSY388

... the Synapse (cont’d.) • Transmission across the synaptic cleft which is only 20 to 30 nanometers wide by a neurotransmitter takes fewer than .01 microseconds • Most individual neurons release at least two or more different kinds of neurotransmitters • The combination makes the neuron’s message more ...
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Concept learning

Concept learning, also known as category learning, concept attainment, and concept formation, is largely based on the works of the cognitive psychologist Jerome Bruner. Bruner, Goodnow, & Austin (1967) defined concept attainment (or concept learning) as ""the search for and listing of attributes that can be used to distinguish exemplars from non exemplars of various categories."" More simply put, concepts are the mental categories that help us classify objects, events, or ideas, building on the understanding that each object, event, or idea has a set of common relevant features. Thus, concept learning is a strategy which requires a learner to compare and contrast groups or categories that contain concept-relevant features with groups or categories that do not contain concept-relevant features.Concept learning also refers to a learning task in which a human or machine learner is trained to classify objects by being shown a set of example objects along with their class labels. The learner simplifies what has been observed by condensing it in the form of an example. This simplified version of what has been learned is then applied to future examples. Concept learning may be simple or complex because learning takes place over many areas. When a concept is difficult, it is less likely that the learner will be able to simplify, and therefore will be less likely to learn. Colloquially, the task is known as learning from examples. Most theories of concept learning are based on the storage of exemplars and avoid summarization or overt abstraction of any kind.
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