def TEST_2(expected): from lab3 import alpha_beta_search tup_tree = ("A", None, ("B", None, ("C", None, ("D", 6), ("E", 4)), ("F", None, ("G", 8), ("H", 6)) ), ("I", None, ("J", None, ("K", 4), ("L", 0)), ("M", None, ("N", 2), ("O", 2)) ) ) tree = make_tree(tup_tree) print "%s:\n%s" % ("TREE_2", tree_as_string(tree)) v = alpha_beta_search(tree, 10, tree_eval, tree_get_next_move, is_leaf) print "BEST MOVE: %s" % (v) print "EXPECTED: %s" % (expected)
def TEST_ALPHA_BETA(): from lab3 import alpha_beta_search tup_tree = ("A", None, ("B", None, ("C", None, ("D", 2), ("E", 12)), ("F", None, ("G", 9), ("H", 4)) ), ("I", None, ("J", None, ("K", 8), ("L", 1)), ("M", None, ("N", 4), ("O", 1)) ) ) tree = make_tree(tup_tree) print "%s:\n%s" % ("TREE_1", tree_as_string(tree)) v = alpha_beta_search(tree, 10, tree_eval_minimax, tree_get_next_move, is_leaf) print "NEXT STEP: %s" % (v)
def TEST_3(expected): from lab3 import alpha_beta_search tup_tree = ("A", None, ("B", None, ("E", None, ("K", 8), ("L", 2)), ("F", 6) ), ("C", None, ("G", None, ("M", None, ("S", 4), ("T", 5)), ("N", 3)), ("H", None, ("O", 9), ("P", None, ("U", 10), ("V", 8)) ), ), ("D", None, ("I", 1), ("J", None, ("Q", None, ("W", 7), ("X", 12)), ("K", None, ("Y", 11), ("Z", 15) ), ) ) ) tree = make_tree(tup_tree) print "%s:\n%s" %("TREE_3", tree_as_string(tree)) v = alpha_beta_search(tree, 10, tree_eval, tree_get_next_move, is_leaf) print "BEST-MOVE:" print v print "EXPECTED:" print expected
def TEST_3(expected): from lab3 import alpha_beta_search tup_tree = ("A", None, ("B", None, ("E", None, ("K", 8), ("L", 2)), ("F", 6)), ( "C", None, ("G", None, ("M", None, ("S", 4), ("T", 5)), ("N", 3)), ("H", None, ("O", 9), ("P", None, ("U", 10), ("V", 8))), ), ("D", None, ("I", 1), ( "J", None, ("Q", None, ("W", 7), ("X", 12)), ("K", None, ("Y", 11), ("Z", 15)), ))) tree = make_tree(tup_tree) print "%s:\n%s" % ("TREE_3", tree_as_string(tree)) v = alpha_beta_search(tree, 10, tree_eval, tree_get_next_move, is_leaf) print "BEST-MOVE: %s" % (v) print "EXPECTED: %s" % (expected)