Artificial IntelligenceA revision of an established text for undergraduate and postgraduate Artificial Intelligence courses, this text incorporates the latest research and methods. |
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Page 78
... Suppose we resolve this in favor of the path we are currently following . Then we will expand E next . Suppose it too has a single successor F , also judged to be three moves from a goal . We are clearly using up moves and making no ...
... Suppose we resolve this in favor of the path we are currently following . Then we will expand E next . Suppose it too has a single successor F , also judged to be three moves from a goal . We are clearly using up moves and making no ...
Page 139
... Suppose , for example , that , in addition to the facts we already have , we add the following . ' Pompeian ( Paulus ) [ loyalto ( Paulus , Caesar ) V hate ( Paulus . Caesar ) ] In other words , suppose we want to make Paulus an ...
... Suppose , for example , that , in addition to the facts we already have , we add the following . ' Pompeian ( Paulus ) [ loyalto ( Paulus , Caesar ) V hate ( Paulus . Caesar ) ] In other words , suppose we want to make Paulus an ...
Page 220
... suppose we do pick one . Suppose , in particular , that we choose to believe that Babbitt's brother - in - law lied . What should be the justification for that belief ? If we believe it just because not believing it leads to a ...
... suppose we do pick one . Suppose , in particular , that we choose to believe that Babbitt's brother - in - law lied . What should be the justification for that belief ? If we believe it just because not believing it leads to a ...
Contents
What Is Artificial Intelligence? | 3 |
5 | 24 |
Heuristic Search Techniques | 63 |
Copyright | |
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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