A New Direction in AI: Toward a Computational Theory of Perceptions

By Lotfi A. Zadeh. The AI Magazine, 2001

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The 2009 Simulated Car Racing Championship (2010, methodology): “Table IV reports the results of the qualifying stage and includes (as a reference) the performance of the example driver (SimpleDriver) distributed with the competition software and the best hand-coded controller provided in TORCS (Berniw).”
Incomplete Multigranulation Rough Set (2010, methodology): “Rough-set methodology presents a novel paradigm to deal with uncertainty and has been applied to feature selection [18], [48], [49], knowledge reduction [9], [16], [51], rule extraction [1], [8], [35], [50], [59], uncertainty reasoning [20], [25], [31], decision evaluation [36]–[38], and granular co”
Fuzzy probabilistic approximation spaces and their information measures (2006, methodology): “Rough set methodology presents a novel paradigm to deal with uncertainty and has been applied to feature selection [1], [2], knowledge reduction [3], [36], [38], rule extraction [4]–[6], uncertainty reasoning [7], [8] and granulation computing [9], [33], [34], [42].”
Is there a need for fuzzy logic? (2008, methodology): “The formalisms of computing with words and perceptions, and NL-Computation were introduced in my l999 paper ‘‘From computing with numbers to computing with words – from manipulation of measurements to manipulation of perceptions” [99]; and developed further in ‘‘A new direction in AI – toward a comp”