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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:
Human-based computation (apart from the historical meaning of "computer") research has its origins in the early work on interactive evolutionary computation (EC). [9] The idea behind interactive evolutionary algorithms has been attributed to Richard Dawkins; in the Biomorphs software accompanying his book The Blind Watchmaker (Dawkins, 1986) [10] the preference of a human experimenter is used ...
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.
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
Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence.It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics.
Natural Language Processing with Python. O'Reilly Media. ISBN 978-0-596-51649-9. Daniel Jurafsky and James H. Martin (2008). Speech and Language Processing, 2nd edition. Pearson Prentice Hall. ISBN 978-0-13-187321-6. Mohamed Zakaria KURDI (2016). Natural Language Processing and Computational Linguistics: speech, morphology, and syntax, Volume 1 ...
MoCap pre-processing 660 action samples 8 PhaseSpace Motion Capture, 2 Stereo Cameras, 4 Quad Cameras, 6 accelerometers, 4 microphones Action classification 2013 [129] Ofli, F. et al. THUMOS Dataset Large video dataset for action classification. Actions classified and labeled. 45M frames of video Video, images, text Classification, action detection
Distributed data processing. Distributed data processing [1] (DDP) [2] was the term that IBM used for the IBM 3790 (1975) and its successor, the IBM 8100 (1979). Datamation described the 3790 in March 1979 as "less than successful." [3] [4] Distributed data processing was used by IBM to refer to two environments: IMS DB/DC; CICS/DL/I [5] [6]