Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas A revision of an established text for undergraduate and postgraduate Artificial Intelligence courses, this text incorporates the latest research and methods. |
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Página 26
... intelligence or can think is too nebulous to answer precisely . But it is often possible to construct a computer program that meets some performance ... Artificial 26 CHAPTER 1. WHAT IS ARTIFICIAL INTELLIGENCE ? 6 Some General References.
... intelligence or can think is too nebulous to answer precisely . But it is often possible to construct a computer program that meets some performance ... Artificial 26 CHAPTER 1. WHAT IS ARTIFICIAL INTELLIGENCE ? 6 Some General References.
Página 589
... Artificial Intelligence , ed . J. Kowalik . Boston : Kluwer . Gale , W. A. , ed . 1986. Artificial Intelligence and Statistics . Reading , MA : Addison - Wesley . Gardner , H. 1985. The Mind's New Science . New York : Basic Books ...
... Artificial Intelligence , ed . J. Kowalik . Boston : Kluwer . Gale , W. A. , ed . 1986. Artificial Intelligence and Statistics . Reading , MA : Addison - Wesley . Gardner , H. 1985. The Mind's New Science . New York : Basic Books ...
Página 595
... Artificial Intelligence 39 ( 1 ) . Marr , D. 1982. Vision : A computational investigation into the human representation and processing of visual information . San Francisco : W. H. Freeman . Martelli , A. 1977. On the complexity of ...
... Artificial Intelligence 39 ( 1 ) . Marr , D. 1982. Vision : A computational investigation into the human representation and processing of visual information . San Francisco : W. H. Freeman . Martelli , A. 1977. On the complexity of ...
Contenido
What Is Artificial Intelligence? | 3 |
5 | 24 |
Heuristic Search Techniques | 63 |
Derechos de autor | |
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Términos y frases comunes
Abbott agents algorithm answer apply approach ARMEMPTY assertions attributes axioms backpropagation backtracking backward belief best-first search breadth-first search Caesar called Chapter chess clauses complete concept conceptual dependency consider constraints contains contradiction corresponding define depth-first depth-first search described discussed domain example fact function game tree goal grammar graph heuristic Horn clauses important inference inheritance input instance interpretation isa links John justification knowledge base knowledge representation labeled learning Marcus match minimax move MYCIN natural language node object ON(B ON(C operators output parsing particular path perceptron perform players possible preconditions predicate logic problem problem-solving procedure produce PROLOG represent result robot rules script Section semantic semantic net sentence shown in Figure simple slot solution solve specific step structure Suppose syntactic task techniques theorem things tree truth maintenance system understanding variables version space