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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Página 95
... constraint inference rules to the selected node to generate all possible new constraints . 3. If the set of constraints contains a contradiction , then report that this path is a deadend . 4. If the set of constraints describes a ...
... constraint inference rules to the selected node to generate all possible new constraints . 3. If the set of constraints contains a contradiction , then report that this path is a deadend . 4. If the set of constraints describes a ...
Página 96
... constraints . Then choose another rule to generate an ad- ditional assignment , which will , in turn , generate new constraints at the next cycle . Of course , at each cycle , there may be several choices of rules to apply . A few ...
... constraints . Then choose another rule to generate an ad- ditional assignment , which will , in turn , generate new constraints at the next cycle . Of course , at each cycle , there may be several choices of rules to apply . A few ...
Página 351
... constraints in problem solving : 1. Analyze the problem domain to determine what the constraints are . 2. Solve the problem by applying a constraint satisfaction algorithm that ef- fectively uses the constraints from step 1 to control ...
... constraints in problem solving : 1. Analyze the problem domain to determine what the constraints are . 2. Solve the problem by applying a constraint satisfaction algorithm that ef- fectively uses the constraints from step 1 to control ...
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A.I. programs algorithm answer applied approach appropriate arcs ARMEMPTY Artificial Intelligence backtracking best-first search blocks world branching factor breadth-first search Caesar Chapter chess clauses CLEAR(A complete concept conceptual dependency consider constraints contains database described discussed domain example exploit explore fact frame game tree goal grammar graph heuristic heuristic function important input INTERLISP ISA links John knowledge representation labelings LISP Marcus match methods minimax move MYCIN natural language necessary 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 understanding variety