Artificial Intelligence, Volumen1McGraw-Hill, 1983 - 436 páginas What is artificial intelligence?; Problem solving; Problems and problem spaces; Basic problem-solving methods; Game playing; Knowledge representation; Knowledge representation using predicate logic; Knowledge representation using other logics; Structured representation of knowledge; Advanced topics; Advanced problem-solving systems; Natural language understanding; Perception; Learning; Implementing A.lI. systems: languages and machines; Conclusion; References; Index. |
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... subgoals . A simple example of this failure is shown in Figure 3-21 . Assuming that both node C and node E ... sub- goals will be presented . 3.6.7 Constraint Satisfaction Many problems in A.I. can be viewed as problems of constraint ...
... subgoals . A simple example of this failure is shown in Figure 3-21 . Assuming that both node C and node E ... sub- goals will be presented . 3.6.7 Constraint Satisfaction Many problems in A.I. can be viewed as problems of constraint ...
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... subgoals . Each of them , in turn , may lead to a set of ad- ditional subgoals . Sometimes it is easy to detect that there is no way that a given set of subgoals can all be satisfied at once . For example , the robot arm cannot be both ...
... subgoals . Each of them , in turn , may lead to a set of ad- ditional subgoals . Sometimes it is easy to detect that there is no way that a given set of subgoals can all be satisfied at once . For example , the robot arm cannot be both ...
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... subgoals have already been satisfied . Then it finds all the operators that might satisfy the final subgoal . Of course , each of them may have preconditions that must be met , so a new combined goal must be generated including those ...
... subgoals have already been satisfied . Then it finds all the operators that might satisfy the final subgoal . Of course , each of them may have preconditions that must be met , so a new combined goal must be generated including those ...
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A.I. programs algorithm answer applied approach appropriate arcs ARMEMPTY Artificial Intelligence backtracking best-first search branching factor breadth-first search Chapter chess clauses CLEAR(A complete Computer concept conceptual dependency consider constraints contains database described discussed domain example expert systems exploit explore fact frame game tree goal grammar graph heuristic heuristic function important input INTERLISP ISA links John knowledge representation labelings learning LISP machine Marcus match methods minimax move MYCIN natural language node objects ON(B operators parsing particular path performed possible preconditions predicate logic probabilistic problem problem-solving produce production system PROLOG propositional logic question reasoning representing knowledge rules Schank script search procedure search process Section semantic net sentence shown in Figure simple situation slots solution solve specific stack statements step strategy structure successors Suppose syntactic task techniques theorem things tion tree true variety