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Problem Representation and Search Principles
Brute Force Strategies
6 other sections not shown
activation function analysis AND/OR graphs artificial intelligence assigned backtracking backtracking algorithm best-first strategy branching factor chromosomes constraint satisfaction problems contains convergence cost function defined delete denotes depth first strategy described determine edge consistency element empty OPEN EURISKO examined nodes execution figure finding a solution finite fitness function game strategy game tree genetic algorithm genetic operators goal node graph search heuristic estimate heuristic function hypergraph initial node iterative deepening knowledge representation leaf level node limit macro operations matching member nprim minimal minimal spanning tree minimax network of constraints neural networks nodes examined nprim nprim->g number of nodes optimal solution p->next parameters Pearl 84 player possible presented procedure processors programs pruning algorithm queens problem representation return NULL rules satisfied schema scout algorithm search algorithms search methods search space selection sequence solution path solution tree successors terminal node variable