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Distributed practice (also known as spaced repetition, the spacing effect, or spaced practice) is a learning strategy, where practice is broken up into a number of short sessions over a longer period of time.
Distributed cognition is an approach to cognitive science research that was developed by cognitive anthropologist Edwin Hutchins during the 1990s. [1]From cognitive ethnography, Hutchins argues that mental representations, which classical cognitive science held that are within the individual brain, are actually distributed in sociocultural systems that constitute the tools to think and ...
The objectives of Distributed Artificial Intelligence are to solve the reasoning, planning, learning and perception problems of artificial intelligence, especially if they require large data, by distributing the problem to autonomous processing nodes (agents). To reach the objective, DAI requires:
The International Parallel and Distributed Processing Symposium (or IPDPS) is an annual conference for engineers and scientists to present recent findings in the fields of parallel processing and distributed computing. In addition to technical sessions of submitted paper presentations, the meeting offers workshops, tutorials, and commercial ...
Stream processing is especially suitable for applications that exhibit three application characteristics: [citation needed] Compute intensity, the number of arithmetic operations per I/O or global memory reference. In many signal processing applications today it is well over 50:1 and increasing with algorithmic complexity.
In the middle of Sternberg's theory is cognition and with that is information processing. In Sternberg's theory, he says that information processing is made up of three different parts, meta components, performance components, and knowledge-acquisition components. [2] These processes move from higher-order executive functions to lower-order ...
The RM-ODP view model, which provides five generic and complementary viewpoints on the system and its environment.. Reference Model of Open Distributed Processing (RM-ODP) is a reference model in computer science, which provides a co-ordinating framework for the standardization of open distributed processing (ODP).
Distributed computing is a field of computer science that studies distributed systems, defined as computer systems whose inter-communicating components are located on different networked computers. [1] [2] The components of a distributed system communicate and coordinate their actions by passing messages to