mt_srand 在游戏开发中怎么用于分配角色属性，实现随机但公平的设定？

gitbox 2025-08-30

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<h1>mt_srand 在游戏开发中怎么用于分配角色属性，实现随机但公平的设定？</h1>

<p><strong>摘要</strong>：<code>mt_srand()

说明：不要用 time() 直接播种，否则同秒内会“撞种”。不要把 mt_srand() 反复调用在一段分配流程里——在一次分配过程开始时播种一次即可。

三、属性点“总量固定”的公平分割：随机切割法（Random Cut / Stars and Bars）

场景：有 6 个属性（力、敏、智、体、运、意志），总点数固定为 30，每项需在 [1,10] 区间。


/**
 * 将 totalPoints 按均匀随机切成 n 份，满足每份均 ≥ minVal、≤ maxVal，且总和不变。
 * 若限制过紧导致不可行，自动回退重尝试（最多 retries 次）。
 */
function random_partition_constrained(int </span><span><span class="hljs-subst">$n</span></span><span>, int </span><span><span class="hljs-subst">$totalPoints</span></span><span>, int </span><span><span class="hljs-subst">$minVal</span></span><span>, int </span><span><span class="hljs-subst">$maxVal</span></span><span>, int </span><span><span class="hljs-subst">$retries</span></span><span> = 256): array {
    for (</span><span><span class="hljs-subst">$t</span></span><span> = 0; </span><span><span class="hljs-subst">$t</span></span><span> &lt; </span><span><span class="hljs-subst">$retries</span></span><span>; </span><span><span class="hljs-subst">$t</span></span><span>++) {
        // 先扣掉下限，剩余 R 进行自由分配
        </span><span><span class="hljs-subst">$R</span></span><span> = </span><span><span class="hljs-subst">$totalPoints</span></span><span> - </span><span><span class="hljs-subst">$n</span></span><span> * </span><span><span class="hljs-subst">$minVal</span></span><span>;
        if (</span><span><span class="hljs-subst">$R</span></span><span> &lt; 0) throw new InvalidArgumentException('下限之和超过总点数');
        // 生成 n-1 个“切点”，对 [0, R] 进行均匀切割
        </span><span><span class="hljs-subst">$cuts</span></span><span> = [];
        for (</span><span><span class="hljs-subst">$i</span></span><span> = 0; </span><span><span class="hljs-subst">$i</span></span><span> &lt; </span><span><span class="hljs-subst">$n</span></span><span> - 1; </span><span><span class="hljs-subst">$i</span></span><span>++) { </span><span><span class="hljs-subst">$cuts</span></span><span>[] = mt_rand(0, </span><span><span class="hljs-subst">$R</span></span><span>); }
        sort(</span><span><span class="hljs-subst">$cuts</span></span><span>);
        </span><span><span class="hljs-subst">$parts</span></span><span> = [];
        </span><span><span class="hljs-subst">$prev</span></span><span> = 0;
        foreach (</span><span><span class="hljs-subst">$cuts</span></span><span> as </span><span><span class="hljs-subst">$c</span></span><span>) { </span><span><span class="hljs-subst">$parts</span></span><span>[] = </span><span><span class="hljs-subst">$c</span></span><span> - </span><span><span class="hljs-subst">$prev</span></span><span>; </span><span><span class="hljs-subst">$prev</span></span><span> = </span><span><span class="hljs-subst">$c</span></span><span>; }
        </span><span><span class="hljs-subst">$parts</span></span><span>[] = </span><span><span class="hljs-subst">$R</span></span><span> - </span><span><span class="hljs-subst">$prev</span></span><span>;
        // 加回下限，并检查上限
        </span><span><span class="hljs-subst">$vals</span></span><span> = array_map(fn(</span><span><span class="hljs-subst">$x</span></span><span>) =&gt; </span><span><span class="hljs-subst">$x</span></span><span> + </span><span><span class="hljs-subst">$minVal</span></span><span>, </span><span><span class="hljs-subst">$parts</span></span><span>);
        if (max(</span><span><span class="hljs-subst">$vals</span></span><span>) &lt;= </span><span><span class="hljs-subst">$maxVal</span></span><span>) return </span><span><span class="hljs-subst">$vals</span></span><span>;
    }
    throw new RuntimeException('在约束下未能找到分割，请放宽上下限或增加总点数。');
}

// 示例：6 项属性，总 30 点，每项 [1,10]
</span><span><span class="hljs-subst">$attrs</span></span><span> = random_partition_constrained(n: 6, totalPoints: 30, minVal: 1, maxVal: 10);
// </span><span><span class="hljs-subst">$attrs</span></span><span> 形如 [7, 4, 2, 6, 3, 8]，总和恒为 30，且均在区间内

该方法具备三个优点：总和严格受控、各项无偏（在约束可行的前提下）、实现简洁。需要注意的是，当 maxVal 太小或 minVal 太大导致可行域很窄时，可能多次重采样才命中。

四、偏好与稀有度：加权无偏抽取（Alias 或分段采样）

如果不同属性希望有不同“权重”（例如“运气”稍稀有），可以按权重抽取额外的“加成点”。下面是简单、易读的分段采样方案（严格按权重无偏）：


/**
 * 根据权重数组返回索引（无偏）
 * @param array&lt;float&gt; </span><span><span class="hljs-subst">$weights</span></span><span> 非负，至少一项 &gt; 0
 */
function weighted_pick(array </span><span><span class="hljs-subst">$weights</span></span><span>): int {
    </span><span><span class="hljs-subst">$sum</span></span><span> = array_sum(</span><span><span class="hljs-subst">$weights</span></span><span>);
    if (</span><span><span class="hljs-subst">$sum</span></span><span> &lt;= 0) throw new InvalidArgumentException('权重总和必须 &gt; 0');
    </span><span><span class="hljs-subst">$r</span></span><span> = mt_rand() / mt_getrandmax() * </span><span><span class="hljs-subst">$sum</span></span><span>; // [0, sum)
    </span><span><span class="hljs-subst">$acc</span></span><span> = 0.0;
    foreach (</span><span><span class="hljs-subst">$weights</span></span><span> as </span><span><span class="hljs-subst">$i</span></span><span> =&gt; </span><span><span class="hljs-subst">$w</span></span><span>) {
        </span><span><span class="hljs-subst">$acc</span></span><span> += </span><span><span class="hljs-subst">$w</span></span><span>;
        if (</span><span><span class="hljs-subst">$r</span></span><span> &lt; </span><span><span class="hljs-subst">$acc</span></span><span>) return </span><span><span class="hljs-subst">$i</span></span><span>;
    }
    return array_key_last(</span><span><span class="hljs-subst">$weights</span></span><span>); // 漂移保护
}

// 示例：给随机分割的 6 项再附加 3 点“稀有加成”，权重偏向第 6 项（意志）
</span><span><span class="hljs-subst">$weights</span></span><span> = [1,1,1,1,1,2.5];
</span><span><span class="hljs-subst">$bonus</span></span><span> = [0,0,0,0,0,0];
for (</span><span><span class="hljs-subst">$k</span></span><span> = 0; </span><span><span class="hljs-subst">$k</span></span><span> &lt; 3; </span><span><span class="hljs-subst">$k</span></span><span>++) {
    </span><span><span class="hljs-subst">$idx</span></span><span> = weighted_pick(</span><span><span class="hljs-subst">$weights</span></span><span>);
    </span><span><span class="hljs-subst">$bonus</span></span><span>[</span><span><span class="hljs-subst">$idx</span></span><span>] += 1;
}

五、控制波动：使用“近似正态”的随机（Box–Muller）

有时你希望“多数中庸、少数极端”。可用 Box–Muller 将均匀分布转为正态分布，再裁剪到区间内：


// 生成 ~N(0,1)
function randn(): float {
    do {
        </span><span><span class="hljs-subst">$u</span></span><span> = mt_rand() / mt_getrandmax();
        </span><span><span class="hljs-subst">$v</span></span><span> = mt_rand() / mt_getrandmax();
    } while (</span><span><span class="hljs-subst">$u</span></span><span> == 0.0); // 避免 log(0)
    return sqrt(-2.0 * log(</span><span><span class="hljs-subst">$u</span></span><span>)) * cos(2.0 * M_PI * </span><span><span class="hljs-subst">$v</span></span><span>);
}

// 在 [min, max] 上产生“钟形”分布
function randn_clamped(float </span><span><span class="hljs-subst">$min</span></span><span>, float </span><span><span class="hljs-subst">$max</span></span><span>, float </span><span><span class="hljs-subst">$mean</span></span><span>, float </span><span><span class="hljs-subst">$std</span></span><span>): float {
    </span><span><span class="hljs-subst">$x</span></span><span> = </span><span><span class="hljs-subst">$mean</span></span><span> + </span><span><span class="hljs-subst">$std</span></span><span> * randn();
    return max(</span><span><span class="hljs-subst">$min</span></span><span>, min(</span><span><span class="hljs-subst">$max</span></span><span>, </span><span><span class="hljs-subst">$x</span></span><span>));
}

做法：先用随机切割保证“总量公平”，再对每个属性加上一个零和的正态微调（正负相抵，保持总和不变），以塑造“多数中庸、少量突出”的体感。

六、多人竞争的“公平分配”：先洗牌再发放

例如 4 名玩家抢 4 套“预生成”的属性模板，可以：

用 matchId 为整局播种；
预生成 4 套模板；
按玩家入场顺序的哈希进行 Fisher–Yates 洗牌，一人一套，避免“座位优势”。


// Fisher–Yates 洗牌：无偏
function shuffle_unbiased(array &amp;</span><span><span class="hljs-subst">$arr</span></span><span>): void {
    </span><span><span class="hljs-subst">$n</span></span><span> = count(</span><span><span class="hljs-subst">$arr</span></span><span>);
    for (</span><span><span class="hljs-subst">$i</span></span><span> = </span><span><span class="hljs-subst">$n</span></span><span> - 1; </span><span><span class="hljs-subst">$i</span></span><span> &gt; 0; </span><span><span class="hljs-subst">$i</span></span><span>--) {
        </span><span><span class="hljs-subst">$j</span></span><span> = mt_rand(0, </span><span><span class="hljs-subst">$i</span></span><span>);
        [</span><span><span class="hljs-subst">$arr</span></span><span>[</span><span><span class="hljs-subst">$i</span></span><span>], </span><span><span class="hljs-subst">$arr</span></span><span>[</span><span><span class="hljs-subst">$j</span></span><span>]] = [</span><span><span class="hljs-subst">$arr</span></span><span>[</span><span><span class="hljs-subst">$j</span></span><span>], </span><span><span class="hljs-subst">$arr</span></span><span>[</span><span><span class="hljs-subst">$i</span></span><span>]];
    }
}

// 预生成模板 + 洗牌分配
</span><span><span class="hljs-subst">$seed</span></span><span> = seed_from_context('ROOM-9F2A', 12, 'ALL'); // 用 ALL 代表整局
mt_srand(</span><span><span class="hljs-subst">$seed</span></span><span>);
</span><span><span class="hljs-subst">$templates</span></span><span> = [];
for (</span><span><span class="hljs-subst">$t</span></span><span> = 0; </span><span><span class="hljs-subst">$t</span></span><span> &lt; 4; </span><span><span class="hljs-subst">$t</span></span><span>++) {
    </span><span><span class="hljs-subst">$templates</span></span><span>[] = random_partition_constrained(6, 30, 1, 10);
}
shuffle_unbiased(</span><span><span class="hljs-subst">$templates</span></span><span>);
// 之后按玩家顺序一人取一个模板（或用玩家ID再做一次稳定洗牌）

七、验证“长期公平”的做法

上线前做 Monte Carlo 验证：

固定一组上下文集合（不同玩家/房间/赛季），跑 10w 次；
统计每个属性的均值、方差、命中上下限的频率；
对权重选择做卡方检验（或至少做频率差距的置信区间估计）；
检查是否存在相关性（例如某属性与玩家ID的不期望耦合）。


// 粗略统计均值（示意）
function simulate_means(int </span><span><span class="hljs-subst">$runs</span></span><span> = 100000): array {
    </span><span><span class="hljs-subst">$sum</span></span><span> = array_fill(0, 6, 0.0);
    for (</span><span><span class="hljs-subst">$i</span></span><span> = 0; </span><span><span class="hljs-subst">$i</span></span><span> &lt; </span><span><span class="hljs-subst">$runs</span></span><span>; </span><span><span class="hljs-subst">$i</span></span><span>++) {
        mt_srand(</span><span><span class="hljs-subst">$i</span></span><span>); // 不同种子
        </span><span><span class="hljs-subst">$vals</span></span><span> = random_partition_constrained(6, 30, 1, 10);
        for (</span><span><span class="hljs-subst">$k</span></span><span> = 0; </span><span><span class="hljs-subst">$k</span></span><span> &lt; 6; </span><span><span class="hljs-subst">$k</span></span><span>++) { </span><span><span class="hljs-subst">$sum</span></span><span>[</span><span><span class="hljs-subst">$k</span></span><span>] += </span><span><span class="hljs-subst">$vals</span></span><span>[</span><span><span class="hljs-subst">$k</span></span><span>]; }
    }
    return array_map(fn(</span><span><span class="hljs-subst">$x</span></span><span>) =&gt; </span><span><span class="hljs-subst">$x</span></span><span> / </span><span><span class="hljs-subst">$runs</span></span><span>, </span><span><span class="hljs-subst">$sum</span></span><span>);
}

八、工程与安全注意

一次流程一次播种：避免在同一流程中多次 mt_srand() 导致相关性。
不要用 mt_rand() 做安全用途：涉及经济价值（开箱、交易、竞赛排名）或反作弊判定时，改用 random_int()（CSPRNG）。
跨语言一致性：服务端和客户端若都参与随机，务必统一算法与参数，或只在服务端做随机并下发结果。
版本固化：种子混入 $salt='v1' 一类的“版本号”以便将来调整算法而不破坏旧回放。

九、整合示例（可复现、总量固定、带权重微调）


function assign_attributes(string </span><span><span class="hljs-subst">$matchId</span></span><span>, int </span><span><span class="hljs-subst">$season</span></span><span>, string </span><span><span class="hljs-subst">$playerId</span></span><span>): array {
    // 1) 播种
    mt_srand(seed_from_context(</span><span><span class="hljs-subst">$matchId</span></span><span>, </span><span><span class="hljs-subst">$season</span></span><span>, </span><span><span class="hljs-subst">$playerId</span></span><span>, 'attr-v1'));

    // 2) 基础分割：6 项、总 30、每项 [1, 10]
    </span><span><span class="hljs-subst">$attrs</span></span><span> = random_partition_constrained(6, 30, 1, 10);

    // 3) 稀有加成：偏好第 6 项
    </span><span><span class="hljs-subst">$weights</span></span><span> = [1,1,1,1,1,2.5];
    for (</span><span><span class="hljs-subst">$i</span></span><span> = 0; </span><span><span class="hljs-subst">$i</span></span><span> &lt; 3; </span><span><span class="hljs-subst">$i</span></span><span>++) { </span><span><span class="hljs-subst">$attrs</span></span><span>[weighted_pick(</span><span><span class="hljs-subst">$weights</span></span><span>)] += 1; }

    // 4) 零和微调（保持总和不变，塑造“多数中庸”）
    </span><span><span class="hljs-subst">$mean</span></span><span> = array_sum(</span><span><span class="hljs-subst">$attrs</span></span><span>) / count(</span><span><span class="hljs-subst">$attrs</span></span><span>);
    </span><span><span class="hljs-subst">$delta</span></span><span> = 0.0;
    for (</span><span><span class="hljs-subst">$k</span></span><span> = 0; </span><span><span class="hljs-subst">$k</span></span><span> &lt; count(</span><span><span class="hljs-subst">$attrs</span></span><span>); </span><span><span class="hljs-subst">$k</span></span><span>++) {
        </span><span><span class="hljs-subst">$adj</span></span><span> = (int) round(randn() * 0.6); // 小幅波动，标准差可调
        </span><span><span class="hljs-subst">$attrs</span></span><span>[</span><span><span class="hljs-subst">$k</span></span><span>] += </span><span><span class="hljs-subst">$adj</span></span><span>;
        </span><span><span class="hljs-subst">$delta</span></span><span> += </span><span><span class="hljs-subst">$adj</span></span><span>;
    }
    // 抵消总和偏移（把舍入误差匀回去）
    while (</span><span><span class="hljs-subst">$delta</span></span><span> != 0) {
        </span><span><span class="hljs-subst">$idx</span></span><span> = mt_rand(0, count(</span><span><span class="hljs-subst">$attrs</span></span><span>)-1);
        if (</span><span><span class="hljs-subst">$delta</span></span><span> &gt; 0 &amp;&amp; </span><span><span class="hljs-subst">$attrs</span></span><span>[</span><span><span class="hljs-subst">$idx</span></span><span>] &gt; 1) { </span><span><span class="hljs-subst">$attrs</span></span><span>[</span><span><span class="hljs-subst">$idx</span></span><span>]--; </span><span><span class="hljs-subst">$delta</span></span><span>--; }
        elseif (</span><span><span class="hljs-subst">$delta</span></span><span> &lt; 0) { </span><span><span class="hljs-subst">$attrs</span></span><span>[</span><span><span class="hljs-subst">$idx</span></span><span>]++; </span><span><span class="hljs-subst">$delta</span></span><span>++; }
    }

    // 5) 裁剪区间（如被裁剪，等额从/向其他项借还，保持总和）
    </span><span><span class="hljs-subst">$min</span></span><span> = 1; </span><span><span class="hljs-subst">$max</span></span><span> = 12;
    </span><span><span class="hljs-subst">$sumBefore</span></span><span> = array_sum(</span><span><span class="hljs-subst">$attrs</span></span><span>);
    </span><span><span class="hljs-subst">$attrs</span></span><span> = array_map(fn(</span><span><span class="hljs-subst">$v</span></span><span>) =&gt; max(</span><span><span class="hljs-subst">$min</span></span><span>, min(</span><span><span class="hljs-subst">$max</span></span><span>, </span><span><span class="hljs-subst">$v</span></span><span>)), </span><span><span class="hljs-subst">$attrs</span></span><span>);
    </span><span><span class="hljs-subst">$sumAfter</span></span><span> = array_sum(</span><span><span class="hljs-subst">$attrs</span></span><span>);
    // 归还或补齐
    </span><span><span class="hljs-subst">$diff</span></span><span> = </span><span><span class="hljs-subst">$sumBefore</span></span><span> - </span><span><span class="hljs-subst">$sumAfter</span></span><span>;
    while (</span><span><span class="hljs-subst">$diff</span></span><span> != 0) {
        </span><span><span class="hljs-subst">$i</span></span><span> = mt_rand(0, count(</span><span><span class="hljs-subst">$attrs</span></span><span>)-1);
        if (</span><span><span class="hljs-subst">$diff</span></span><span> &gt; 0 &amp;&amp; </span><span><span class="hljs-subst">$attrs</span></span><span>[</span><span><span class="hljs-subst">$i</span></span><span>] &lt; </span><span><span class="hljs-subst">$max</span></span><span>) { </span><span><span class="hljs-subst">$attrs</span></span><span>[</span><span><span class="hljs-subst">$i</span></span><span>]++; </span><span><span class="hljs-subst">$diff</span></span><span>--; }
        elseif (</span><span><span class="hljs-subst">$diff</span></span><span> &lt; 0 &amp;&amp; </span><span><span class="hljs-subst">$attrs</span></span><span>[</span><span><span class="hljs-subst">$i</span></span><span>] &gt; </span><span><span class="hljs-subst">$min</span></span><span>) { </span><span><span class="hljs-subst">$attrs</span></span><span>[</span><span><span class="hljs-subst">$i</span></span><span>]--; </span><span><span class="hljs-subst">$diff</span></span><span>++; }
    }
    return </span><span><span class="hljs-subst">$attrs</span></span><span>;
}

十、结语

把 mt_srand() 的“种子”与对局上下文绑定，可得到可复现的伪随机；用随机切割、权重采样与零和微调等手法，就能在满足约束的前提下构造随机但公平的属性分配。若涉及价值博弈或强对抗场景，考虑切换到 random_int() 等密码学安全的随机源，同时记录“算法版本 + 种子 + 输入”，为争议处理与观战回放提供证据。

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