UniformCost_AI_py:用 Python 实现的统一成本搜索算法

# UniformCost_AI_py Uniform Cost Search Algorithm implemented in Python. This is a school project for Artificial Intelligence. There are 2 versions available. Version "maynard_hw1_r1.py" is a NetworkX implementation that solves the problem with Dijkstra algorithm. Version "maynard_hw1_r5.py" implements the Uniform-Cost Search (UCS) algorithm. The pseudo-code for the algorithm is as follows: # UCS Pseudocode: # Let fringe be a priority queue containing initial state # Loop # if fringe is empty # return failure # node = remove-first(fringe) # if node is goal # return path from initial state to node # else # generate all successors of node and put the newly generated # nodes into fringe according to their cost values # # References: # Korzhova, Lecture 5 # "Artificial Intelligence A Modern Approcah", Russell, Norvig