matlab贪婪最佳优先搜索

贪婪最佳优先搜索（GBFS）是一种启发式搜索算法，它在搜索过程中优先考虑距离目标状态最近的节点。在 MATLAB 中实现 GBFS 的关键是定义好启发函数，即估计当前节点到目标状态的距离。下面是一个简单的 MATLAB 代码示例：

function [path, cost] = gbfs(start, goal, h)
    % start: 起始状态
    % goal: 目标状态
    % h: 启发函数，估计当前状态到目标状态的距离
    % path: 找到的路径
    % cost: 路径的代价

    % 初始化
    open = [start]; % 待扩展节点集合
    closed = []; % 已扩展节点集合
    g = containers.Map({start}, {0}); % 起始状态到当前状态的代价
    f = containers.Map({start}, {h(start)}); % 启发函数值

    while ~isempty(open)
        % 选择 f 值最小的节点进行扩展
        [~, idx] = min(cell2mat(values(f)));
        curr = open(idx);
        open(idx) = [];

        % 如果当前节点是目标状态，则返回路径和代价
        if isequal(curr, goal)
            path = [goal];
            cost = g(goal);
            while ~isequal(path(1), start)
                for s = keys(g)
                    if isequal(s{1}, path(2))
                        if g(s{1}) + h(s{1}) == cost
                            path = [s{1}, path];
                            break;
                        end
                    end
                end
            end
            return;
        end

        % 将当前节点加入已扩展节点集合
        closed = [closed, curr];

        % 扩展当前节点的所有邻居
        neighbors = get_neighbors(curr);
        for i = 1:length(neighbors)
            neighbor = neighbors{i};
            if ~ismember(neighbor, closed) && ~ismember(neighbor, open)
                % 如果邻居不在待扩展节点集合和已扩展节点集合中，则加入待扩展节点集合
                open = [open, neighbor];
                g(neighbor) = g(curr) + 1; % 代价加 1
                f(neighbor) = h(neighbor); % 启发函数值
            end
        end
    end

    % 如果搜索失败，则返回空路径和代价
    path = [];
    cost = Inf;
end

function neighbors = get_neighbors(state)
    % 获取当前状态的所有邻居
    % 这里假设状态是一个字符串，每个字符表示一个位置的状态

    neighbors = {};
    n = length(state);
    for i = 1:n-1
        if state(i) ~= state(i+1)
            neighbor = state;
            neighbor(i:i+1) = fliplr(neighbor(i:i+1)); % 交换相邻两个位置的状态
            neighbors = [neighbors, neighbor];
        end
    end
end