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Operation at the third level of the ETC, the cognitive/symbolic level, requires "complex and sophisticated" information processing, in which the individual consciously and strategically plans—prior to creating the art piece—for an expressive and self-satisfying final product. [3]
MATLAB (an abbreviation of "MATrix LABoratory" [18]) is a proprietary multi-paradigm programming language and numeric computing environment developed by MathWorks.MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages.
Symbolic Math Toolbox MathWorks: 1989 2008 9.4(2018a) 2018: $3,150 (Commercial), $99 (Student Suite), $700 (Academic), $194 (Home) including price of MATLAB. Proprietary: Provides tools for solving and manipulating symbolic math expressions and performing variable-precision arithmetic. SymPy: Ondřej Čertík 2006 2007 1.13.2: 11 August 2024: Free
The symbol grounding problem is a concept in the fields of artificial intelligence, cognitive science, philosophy of mind, and semantics.It addresses the challenge of connecting symbols, such as words or abstract representations, to the real-world objects or concepts they refer to.
Counterexample-guided abstraction refinement (CEGAR) is a technique for symbolic model checking. [1] [2] It is also applied in modal logic tableau calculi algorithms to optimise their efficiency. [3] In computer-aided verification and analysis of programs, models of computation often consist of states. Models for even small programs, however ...
Symbolic data analysis (SDA) is an extension of standard data analysis where symbolic data tables are used as input and symbolic objects are made output as a result. The data units are called symbolic since they are more complex than standard ones, as they not only contain values or categories, but also include internal variation and structure.
Symbolic Neural symbolic—is the current approach of many neural models in natural language processing, where words or subword tokens are both the ultimate input and output of large language models. Examples include BERT, RoBERTa, and GPT-3. Symbolic[Neural]—is exemplified by AlphaGo, where symbolic techniques are used to call neural ...
Shannon's diagram of a general communications system, showing the process by which a message sent becomes the message received (possibly corrupted by noise). seq2seq is an approach to machine translation (or more generally, sequence transduction) with roots in information theory, where communication is understood as an encode-transmit-decode process, and machine translation can be studied as a ...