def part2_rule_2(board, belief_matrix_, target):
"""
:param board: board
:param belief_matrix: belief matrix
:return: number of searches
"""
num_searches = 0
dim = len(board)
prob_found_matrix_ = get_prob_found_matrix(board=board,
belief=belief_matrix_)
next_step = get_max_index(prob_found_matrix_)
while (target[0], target[1]) != next_step:
belief_matrix_ = update_belief_matrix(board=board,
belief=belief_matrix_,
i=next_step[0],
j=next_step[1])
num_searches += 1
prob_found_matrix_ = get_prob_found_matrix(board=board,
belief=belief_matrix_)
# target moved
target, evidence = move_target(dim, target, board)
prob_found_matrix_ = update_found_matrix_by_evidence(
board, prob_found_matrix_, evidence)
next_step = get_max_index(prob_found_matrix_)
return num_searches
def rule_1(board, belief_matrix_, target):
num_searches = 0
next_step = get_max_index(belief_matrix_)
while (target[0], target[1]) != next_step:
belief_matrix_ = update_belief_matrix(board=board,
belief=belief_matrix_,
i=next_step[0],
j=next_step[1])
num_searches += 1
next_step = get_max_index(belief_matrix_)
return num_searches
def rule_1_dis(board, belief_matrix_, target, simple=True):
num_searches = 0
next_step = get_max_index(belief_matrix_)
dim = len(board)
dis_matrix = np.zeros_like(board)
while (target[0], target[1]) != next_step:
belief_matrix_ = update_belief_matrix(board=board,
belief=belief_matrix_,
i=next_step[0],
j=next_step[1])
num_searches += dis_matrix[next_step[0], next_step[1]]
dis_matrix = get_dis(dim, i=next_step[0], j=next_step[1])
if simple == False:
log_dis_matrix = 1 + np.log(1 + dis_matrix)
next_step = get_max_index(belief_matrix_ / log_dis_matrix)
else:
next_step = get_max_index(belief_matrix_)
return num_searches