From 78d52ff81cfd25c7ecdc768bab0a72dc043c4945 Mon Sep 17 00:00:00 2001 From: HelixCopex Date: Fri, 11 Sep 2026 03:26:20 +0800 Subject: [PATCH] =?UTF-8?q?=E7=AC=AC=E4=B8=89=E9=97=AE=E7=9A=84=E5=9E=83?= =?UTF-8?q?=E5=9C=BE=E7=AE=97=E6=B3=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- README.md | 18 +- docs/algo-3.md | 408 ++++++ .../q3/practice/20260911-port2026/actions.csv | 553 ++++++++ .../practice/20260911-port2026/manifest.json | 42 + ...17927797384597197-DHFK-PHD2-SR2P-FXK9.jlog | Bin 0 -> 105193 bytes ...17927797384597197-DHFK-PHD2-SR2P-FXK9.psum | Bin 0 -> 3623 bytes ...7384597197-DHFK-PHD2-SR2P-FXK9.result.json | 1 + .../practice/20260911-port2026/regression.txt | 2 + .../20260911-port2026/replay_summary.json | 110 ++ .../q3/practice/20260911-port2026/report.md | 75 ++ .../practice/20260911-port2026/session.jsonl | 1104 ++++++++++++++++ .../practice/20260911-port2026/summary.json | 111 ++ .../20260911-port2026/verification.json 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output/q3/search-ablation/scenes/random-10-seed3.json create mode 100644 output/q3/search-ablation/scenes/random-10-seed4.json create mode 100644 output/q3/search-ablation/scenes/random-16-seed0.json create mode 100644 output/q3/search-ablation/scenes/random-16-seed1.json create mode 100644 output/q3/search-ablation/scenes/random-16-seed2.json create mode 100644 output/q3/search-ablation/scenes/random-16-seed3.json create mode 100644 output/q3/search-ablation/scenes/random-16-seed4.json create mode 100644 scripts/benchmark_q3_search.py create mode 100644 scripts/run_q3_seven_practice.py create mode 100644 scripts/verify_q3_practice.py diff --git a/README.md b/README.md index fc7b85b..149c821 100644 --- a/README.md +++ b/README.md @@ -6,6 +6,7 @@ - [四问建模分析与 P0–P7 实施计划](docs/B题建模分析与实施计划.md) - [协议规则表、字段表与状态机（P0 交付）](docs/协议规则表与状态机.md) - [问题一完整解答](docs/问题一解答.md) +- [问题三搜索与总耗时改进方案（含七点覆盖证明和自建消融）](docs/algo-3.md) - [论文](docs/paper/main.tex) ## 项目结构 @@ -84,12 +85,27 @@ client.exit() | P1 协议基线（客户端 + 自建回放/故障注入测试） | ✅ 完成 | | P2 几何内核（角域交、直径、MEC、证书） | ✅ 完成（迁入 `mcm26b.geometry`） | | P3 问题二选点（K1、候选区域 Q、采样评估） | ✅ 完成（belief + 选点器，测试固化） | -| P4 问题3全向闭环（49点覆盖、定位队列、清除、停止） | ✅ 自建完成（官方演练待执行） | +| P4 问题3全向闭环（49点覆盖、定位队列、清除、停止） | ✅ 官方问题3演练单案例通过（10/10全清，[验证报告](output/q3/practice/20260911-port2026/report.md)） | | P5 问题4定向扩展（联合约束、后备清除、预算） | ✅ 自建完成（官方演练待执行） | | P6 加速与消融 | 🦴 未开始 | ## 采集与正式测试约束 +改进版 A2（七点覆盖＋本站批量扫频）已通过官方案例 `J4ER-Y9EP-Q379-UPFA`： +12/12源全清，109次检测，虚拟耗时5232.132109秒，现实耗时3.406秒。 +[本局报告与运行方法](output/q3/practice/20260911-seven-batch-01/report.md)。 +独立入口为 `scripts/run_q3_seven_practice.py`，默认 `mcm26b run` 策略仍保持原样。 + +2026-09-11 已通过本机 2026 端口完成一次官方问题3演练：案例 +`DHFK-PHD2-SR2P-FXK9`，10/10 源全清，540 次检测、10 次清除，现实耗时 +7.629 秒。原始请求响应、官方产物及离线审计见上述验证报告。原计时复算的 +541 处微秒精度误报也已记录；按官方整数微秒累计规则独立复算后，552 个 +响应时刻全部吻合。生产计时复算函数保持原样。 + +```bash +uv run python scripts/verify_q3_practice.py output/q3/practice/20260911-port2026 +``` + 本项目只使用官方**演练**采集观测，从未使用正式测试。`scripts/capture_practice.py` 不会启动测试：必须先在界面确认“问题3演练”、接口已就绪，再提供 `--practice-confirmed` 与本局案例编码。正式测试由团队按计划另行安排； diff --git a/docs/algo-3.md b/docs/algo-3.md new file mode 100644 index 0000000..28ce792 --- /dev/null +++ b/docs/algo-3.md @@ -0,0 +1,408 @@ +# 问题三：具有覆盖证明的多源搜索与总耗时优化 + +## 摘要 + +针对源数为10至16、频道互异、位置未知的全向无线电干扰源，建立“发现—定位—清除—完整性证明”的在线决策模型，以全部清除为约束、以移动、检测、换频道和清除的虚拟总耗时为优化目标。沿用问题一的角域交与最小包围圆、问题二的安全接收区域，将改进重点放在全域覆盖规模与多源任务调度。首先从官方演练日志识别移动与无源频道验证的主要开销；随后证明中心加六个环形检测点即可覆盖题设圆域，并提出同站批量扫频、发现任务入队、就近定位清除的可执行基线。进一步规划利用无信号观测维护剩余区域、复用顺路检测点、优化安全清除位置及滚动比较剩余任务耗时的方法。给出停止条件、几何保守性、算法复杂度和分阶段验收方案。12个自建场景的配对消融表明，七点批量策略全部清除成功，平均逐局虚拟时间降幅为58.55%；该结果用于选择下一步实现方向，不作为官方成绩或全局最优性证明。 + +**关键词：** 全向源搜索；覆盖证书；集合定位；任务调度；虚拟总耗时；滚动规划。 + +## 1. 问题界定与思路来源 + +第三问要求在不知道干扰源位置和具体数量的条件下，自动发现并清除全部全向源，尽量缩短总时间。每个频道最多一个源，因此本题的数据关联由频道确定；机器狗无需解决无法区分多个信号身份的问题。源位于半径1800米的圆域内，最小有效接收半径为1000米。这两个尺度之间的关系使稀疏、有证明的覆盖成为可能。[题面](C:/Users/HelixCopex/code/MATH/issue/B题.pdf)、[接口规则](C:/Users/HelixCopex/code/MATH/docs/协议规则表与状态机.md) + +本文与前两问分工如下：问题一回答“当前观测允许源在哪里、能否一次清除”；问题二回答“下一次去哪里测才安全且有效”；问题三回答“先搜哪些位置、扫哪些频道、何时中断搜索去清除，以及何时能够确信任务结束”。全局调度会调用前两问的几何内核，但不能只把第二问的局部精度目标逐个重复就视为总时间优化。 + +参考本项目[问题3—4论文列表](C:/Users/HelixCopex/code/MATH/docs/B题问题3-4相关论文列表.md)，选取并核对以下相关思想。 + +| 来源 | 本文借鉴的内容 | 与本题的区别 | +| --- | --- | --- | +| Bayram、Vander Hook、Isler，2016，列表第10项 | 联合规划测向位置和访问顺序，同时计入移动时间与测量时间 | 原文以GDOP描述不确定度；其近似比不能转移为本文有界角域和清除任务的近似保证 | +| Olofsson等，2020，列表第22项 | 根据已观测区域分配后续搜索资源，在有限预算下规划路径 | 原文使用PHD和期望发现数；本文用确定性的逐频道剩余区域，不用概率很小替代无源证明 | +| Perera等，2023，列表第4项 | 将稀疏覆盖路线与无线电源定位结合，并分别评价路径与采样代价 | 原文依赖RSSI；本题接口没有RSS/RSSI数值，不能直接使用其估计器 | + +上述内容分别见[大学研究记录及论文摘要](https://experts.umn.edu/en/publications/gathering-bearing-data-for-target-localization-6/)、[作者公开论文](https://torarnj.folk.ntnu.no/AURO2020a.pdf)、[arXiv原文入口](https://arxiv.org/abs/2312.03493)。这里只迁移任务组织方法，以下七点几何证明和题目化调度公式在本文独立推导。 + +论文列表中建议的RSS梯度逼近不能直接用于本题：`/measure` 只返回无信号、近距离或示向度，没有连续场强值。Atanasov等的源搜索也依赖场信号、随机梯度或测量模型，其收敛结论不证明本题仅测向闭环收敛。[原论文摘要](https://arxiv.org/abs/1402.0051) 本文也不假定源位置均匀分布、每次误差独立重抽样或某一交会角在所有场景下最优。 + +## 2. 现有方案的实测瓶颈 + +官方问题3演练 `DHFK-PHD2-SR2P-FXK9` 已证明现有实现能在该局全清10个源，完整数据见[演练验证报告](C:/Users/HelixCopex/code/MATH/output/q3/practice/20260911-port2026/report.md)。该局在策略运行结束后才读取官方源数，源真值没有进入决策。 + +| 分项 | 本局数值 | 对改进的含义 | +| --- | ---: | --- | +| 总虚拟时间 | 16217.454814秒 | 作为官方基线，不与自建场景混算 | +| 移动距离 / 耗时 | 64737.274米 / 12947.454814秒 | 移动约占79.84%，应优先减少站点和往返 | +| 检测次数 / 耗时 | 540次 / 2700秒 | 无源频道各扫49点，共490次，占全部检测90.74% | +| 换频道耗时 | 520秒 | 可以优化，但节省一次换频仅相当于少走5米 | +| 清除耗时 | 50秒，10次全部成功 | 清除可靠性已得到单局支持，无需先追求更小定位半径 | +| 最后一个源清除时刻 | 8454.332399秒 | 其后7763.122415秒用于剩余任务，约占总时间47.87% | + +现有 `OmnidirectionalLoop._coverage_phase` 的结构还引入额外往返：在一个覆盖站按频道扫描，遇到 `direction` 就立即定位清除，再回原覆盖站继续下一频道。由原始动作日志统计，从非网格点返回网格检测点共10次，累计约9996.714米、1999.343秒。这是实际行程分类，不能全部当成可直接删除的收益，因为改序后仍需访问下一任务；但它明确说明同站任务应先批量处理。 + +当前49点网格同时服务第三问和第四问。它的定向覆盖证明要求更强的几何条件；第三问无需为未知发射朝向付出同样的采样代价。改进第三问时，应显式区分全向策略和第四问策略，不能全局替换公用网格。 + +## 3. 状态、信息与优化目标 + +### 3.1 符号与可用信息 + +| 符号 | 含义 | +| --- | --- | +| $\Omega=B(0,R)$，$R=1800$ | 源位置区域，单位米 | +| $R_-=1000$，$R_+=1500$ | 有效接收半径下界、上界 | +| $p,f,t$ | 当前机器人位置、测向频道、官方虚拟时刻 | +| $K_c$ | 已发现频道 $c$ 的保守位置候选集 | +| $E_c$ | 尚未发现频道 $c$ 仍可能存在源的位置集合 | +| $\mathcal U,\mathcal D,\mathcal L,\mathcal C,\mathcal A$ | 未发现、待定位、可保证清除、已清除、已证明无源频道集 | +| $\mathcal P$ | 曾获得有效存在证据的不同频道集，包含已清除频道 | +| $\delta=1.005^\circ$ | 题设1°误差加两位小数舍入裕量 | +| $S$ | 具有全域覆盖证明的检测站集合 | +| $L,N_m,N_s,N_c^+,N_c^-$ | 移动长度、检测数、换频数、成功与失败清除数 | + +源静止、同位置同频道的测向误差固定。只有该频道实际收到的观测才能更新其状态；经过一个位置不代表在那里扫过所有频道。不同频道的无信号证据不能互相替代。 + +### 3.2 统一的时间口径 + +忽略微秒量化时，整局虚拟耗时为 + +$$T=\frac{L}{5}+5N_m+N_s+5N_c^++3N_c^-.$$ + +`/clear` 的目标频道不改变测向机频道，因而不引入换频代价；`/exit` 不要求回到原点，也不增加虚拟时间。因此访问顺序是从当前位置出发、终点自由的**开放路径**问题，不能默认使用需要返回起点的旅行商回路。 + +官方内部按微秒累计，验收时按每次移动耗时量化到整数微秒，再累加检测、换频和清除的整数秒。连续实数公式用于规划，逐动作微秒公式用于复算。原演练汇总的541处偏差已查明为累计浮点与微秒精度口径不同，详见[独立审计](C:/Users/HelixCopex/code/MATH/output/q3/practice/20260911-port2026/verification.json)。 + +优化目标按优先级定义为：保持真源候选和有效完成条件；在现实1200秒、虚拟360000秒上限内全清；在可完成策略中降低 $T$。现实计算和网络耗时单独约束，不加进虚拟时间公式。由于源场景和误差场未知，理想模型可写为对允许场景集合 $\Xi$ 的 $\inf_\pi\sup_{\xi\in\Xi}T(\pi,\xi)$，但本文不声称解出了这个连续在线极小极大问题，也不声称已证明任意合法场景都能在两个预算内完成。 + +## 4. 逐频道证据与安全停止 + +### 4.1 观测更新 + +首次 `direction` 在 $s$ 返回 $\theta$ 时，建立 + +$$K_c=\Omega\cap B(s,R_+)\cap W(s,\theta,\delta).$$ + +以后每次有效测向再交入相应距离上界和角域。`near` 时交入 $B(s,5)$，当前检测点本身就满足20米清除条件。角域的半平面表达、保守圆盘外包和最小包围圆计算沿用[问题一](C:/Users/HelixCopex/code/MATH/docs/algo-1.md)、[问题二](C:/Users/HelixCopex/code/MATH/docs/algo-2.md)。 + +全向源在 $s$ 返回 `no_signal`，意味着若该频道仍存在未清除源，则其距离严格大于实际接收半径，进而大于1000米。因此对未发现频道可维护 + +$$E_c=\Omega\setminus\bigcup_{s\in\mathcal N_c}B(s,R_-),$$ + +其中 $\mathcal N_c$ 只含该频道实际测得无信号的位置。有限精度实现可只排除 $B(s,R_- -\eta)$，$\eta>0$ 是有依据的数值裕量；少删不会漏源。该负观测更新仅用于第三问，不能直接用于第四问的定向源。 + +圆盘差通常非凸。不能把扣除圆盘后的集合强行表示成单个凸多边形，更不能丢弃狭窄或小面积分量。第一阶段保留当前凸定位内核，仅在未知频道的覆盖账本中使用负观测；后续如把无信号用于已发现源的精定位，应使用多片区域或再取保守凸外包。 + +### 4.2 完成与计数推理 + +安全停止条件是 $\mathcal C\cup\mathcal A=\{1,\ldots,20\}$，且本局 `/exit` 已被接受。无源证明可来自完整覆盖、剩余集合的可靠判空，或下述数量上界。 + +由于每频道至多一个源且总数不超过16，当 $|\mathcal P|=16$ 时，所有未出现过有效信号的频道即可由数量上界判为无源，**不必等待16个都清除才停止扫未知频道**。随后仍须清除 $\mathcal P\setminus\mathcal C$，不能直接退出。成功清除16个则立即满足全清条件。 + +只发现或清除10个不够，因为10是下界。反过来，若无源证据已排除10个频道，则其余10个频道都必须有源，但仍需获取其定位观测；这种计数推理不能替代位置搜索。若已知存在与无源证据互相矛盾，或可存在频道数不足10，应报告协议、模型或数值不一致，不能把矛盾解释为成功。 + +## 5. 用七个检测站替代49点网格 + +### 5.1 布点 + +取原点及半径 $a$ 圆周上的六个等角点： + +$$S(a)=\{(0,0)\}\cup\{a(\cos(k\pi/3),\sin(k\pi/3)):k=0,\ldots,5\}.$$ + +推荐首个工程版本固定 $a=1200$ 米。站点坐标为 $(0,0)$、$(1200,0)$、$(600,\pm600\sqrt3)$、$(-600,\pm600\sqrt3)$、$(-1200,0)$。这些点全部位于源圆域内；允许域外检测这一规则仍然保留，但本方案不需要依赖它。 + +### 5.2 连续覆盖证明 + +**定理1：** 若 $01800$ 的单元才可直接判为域外；边界相交不确定时继续保留或细分。 + +一次该频道无信号观测位于 $s$，若整个单元满足 + +$$\|z-s\|+h\le1000-\eta,$$ + +则单元全部落入保证可收盘，可以安全删除。不得只检查单元中心，也不得用近似覆盖面积达到100%作为判空证据。若单元仍与真实残余相交，就保留它，直至可给出整单元删除证书。 + +**命题2：** 以上规则维持 $E_c\subseteq\widetilde E_c$，故 $\widetilde E_c=\varnothing$ 足以证明无源。反过来，$\widetilde E_c\ne\varnothing$ 可能只是离散保守性，不能据此断言有源。 + +七点有31.098米几何余量；可使最终方格边长不超过20米，其直径不超过28.285米。对任意与 $\Omega$ 相交的单元，取其中一个域内点，该点距某站不超过968.902米；单元全部点距该站不超过997.186米。因此在工程裕量小于约2.81米且正确处理边界相交的情况下，七站无信号足以最终删除这些单元。这里用整单元的最大距离证书；若只用 $\|z-s\|+h$ 的较松证书仍未通过，继续细分或直接使用七点账本证明，不错误地停在粗格残片上。 + +### 7.2 候选点与频道选择 + +新增候选点来自：未完成的七个锚点、当前位置、已规划的定位点/清除点、残余区域边界附近点。对 $q$ 和频道集合 $F$，定义 + +$$G(q,F)=\sum_{c\in F}\operatorname{area}\bigl(\widetilde E_c\cap B(q,1000-\eta)\bigr),$$ + +并以 $G(q,F)/(\|p-q\|/5+5|F|+N_{\rm switch}(F))$ 作为探索排序指标。面积是搜索潜力代理，不是发现概率或保证的信息增益；面积计算可近似，但只影响候选排序。无源判定仍由整区域覆盖证书给出。对极小、线状或退化残余，还要保留单元数、最远未覆盖距离及锚点完成优先级，不能因面积接近零而永久忽略。 + +在当前位置按每个候选频道的 $G(q,\{c\})$ 与5秒检测、可能1秒换频排序，只有优于当前预演方案时才添加。未来站点若要删除，必须重新证明该频道的剩余 $\widetilde E_c$ 被保留站点的保证接收盘覆盖；一次扫描所得“没有发现”只删该次盘内区域，不能整片按经验跳过。 + +### 7.3 完备后备 + +七点中未完成的“站点—频道”记录始终保留。自适应探索若连续不产生新的可靠覆盖、计算超时或动态证书不确定，则恢复固定七点访问。设置有限的额外探测额度或要求每次替换都完成至少一个新的覆盖记录，使启发式不能无限拖延覆盖完成。 + +这给出确定性的搜索后备：自适应部分只允许节省已证明冗余的动作，不允许删除尚未证明冗余的覆盖责任。该设计尚未进入当前生产实现，也未包含在第12节的七点消融中。 + +## 8. 定位和清除也应优化剩余时间 + +### 8.1 定位到“够清除”就停止 + +设保守多边形 $\widetilde K_c$ 的最小包围圆为 $B(m_c,\rho_c)$。清除阈值使用 $r_{\rm safe}=20-\varepsilon$，其中 $\varepsilon$ 覆盖实际计算和坐标提交误差。若 $\rho_c\le r_{\rm safe}$，就具有一次清除证书；没有必要为了获得更小半径继续增加检测或横移。 + +外包多边形本身已经包含真集，它的多余面积使决策更保守；不能把“外包多边形与原圆盘的径向差”未经传播分析当作浮点误差保证。现有实现还扣除了 `slack_m` 和工程清除余量，本次消融完整保留其行为；后续统一外包与数值误差口径时另行验收。 + +### 8.2 在所有保证清除点中选择短路径位置 + +若 $V_c$ 为 $\widetilde K_c$ 的顶点，则 + +$$\mathcal C_c=\bigcap_{v\in V_c}B(v,r_{\rm safe})$$ + +是凸集，非空当且仅当 $\rho(\widetilde K_c)\le r_{\rm safe}$。圆盘凸性保证覆盖全部顶点等价于覆盖整个多边形，故任意 $q\in\mathcal C_c$ 都能清除真源。 + +无后续任务时，选择 $\arg\min_{q\in\mathcal C_c}\|q-p\|$；已计划下一站 $b$ 时选择 $\arg\min_{q\in\mathcal C_c}(\|p-q\|+\|q-b\|)$。两者都是凸优化问题，可用二阶锥形式表达，也可在圆盘交的候选边界上求解后逐顶点复核。 + +轻量实现可先使用内部安全圆盘 $B(m_c,r_{\rm safe}-\rho_c)\subseteq\mathcal C_c$：将 $p$ 投影到该圆盘即可得到一个不远于前往 $m_c$ 的保证清除点。这只是对该充分圆盘的最近点，并非对整个 $\mathcal C_c$ 最优。若圆盘半径为0就退化到 $m_c$。 + +### 8.3 安全测点的目标由半径改为任务耗时 + +问题二提供的安全区域为 $\mathcal Q(K_c)=\bigcap_{g\in K_c}B(g,1000)$，可用解析盘或保守多边形构造充分区域。选点仍必须先满足接收保证，不能为走近一个猜测坐标而接受未经评估的失联风险。 + +在可安全测量的候选点中，使用以秒计量的短程代价 + +$$J_H(q)=\frac{\|p-q\|}{5}+5+\mathbf1_{f\ne c}+\max_{z\in\mathcal Z(q)}\widehat V_{H-1}(K_c\mid q,z;q,c),$$ + +其中 $z$ 包含 `near` 及允许的示向度，$\widehat V$ 估计完成该源及返回后续任务的时间。若某分支已能保证清除，其终端代价包括移动至 $\mathcal C_c$ 的时间和5秒清除；若未能清除，可继续一层安全测向，或赋予经过标定的剩余定位代价。未来测点、清除位置与访问顺序共同影响 $\widehat V$。 + +这个形式解释了为什么“后验半径更小”不一定“完成更快”：走远很久将半径降到5米，可能劣于近处测量后已经达到19米。所有实际比较项统一为秒，避免随意相加米、面积和时间。有限候选和有限视野只给出预演策略的启发式排序。 + +若要把 $\max_z$ 报告为严格上界，必须采用问题二第10节覆盖全部读数的角区间扩张，并对区域误差与终端代价也作保守上界。当前“边界位置采样×误差端点”并无该保证，不能仅因取了样本最大值就声称最坏总时间已受控。推荐先保留现有局部选点，验证搜索调度收益，再单独启用这一成本模型。 + +## 9. 保守性、有限结束与预算边界 + +**命题3（不漏发现）：** 固定七点对每个仍未知频道完成扫描，或由可靠的残余覆盖/数量证书替代相应扫描，必能发现所有合法全向源。 + +**证明：** 固定点由定理1保证；动态替代保持该频道覆盖域包含所有仍可能位置；数量证书只在已有16个不同源的存在证据时排除其他频道。因此真源不可能被当作无源跳过。证毕。 + +**命题4（证书清除）：** 若维护的外包集合包含真源，实际提交点满足对该外包的20米清除约束，则在题设规则下 `/clear` 必成功。几何证书通过而官方失败时必须记录异常并检查模型、数值及协议状态，不能在同一证书上循环重试。 + +上述命题不证明任意安全测点序列都会有限步收缩到20米。现有每轮8次测量是工程限额，不能作为收敛定理。拟在后续增加有限后备：对已发现频道的有界外包区域，用边长20米方格的中心覆盖所有相交格，任意格内点至格心不超过 $10\sqrt2<20$ 米；遍历该有限清除候选即可在模型成立时清除源。单元相交计算必须向保留更多格的方向保守。 + +后备仅在定位停滞时使用，并须先检查实际枚举格数、路径和预算。设当前到首格及格间的计划路长为 $L_f$，共 $M_f$ 格，最迟第 $M_f$ 格成功的虚拟耗时上界为 + +$$T_f\le L_f/5+3(M_f-1)+5.$$ + +使用相交格数硬顶、现实高分位单请求估计 $M_f\,t_{\rm RTT}^{95}$ 加退出预留，以及虚拟剩余预算共同筛选。现有第四问中的后备格算法可供复用，但不能跳过第三问的验证。硬顶或预算不允许时，保留“未完成”，不将耗尽预算说成证明无源。 + +因此本文区分三层结论：覆盖与证书的数学安全性；预算足够且正确遍历有限后备时的有限完成性；现实/虚拟双预算内的性能，目前由实验评价，尚无所有合法场景的统一完成上界。 + +## 10. 推荐算法与伪代码 + +**算法3A：七点覆盖＋同站批量扫频＋就近定位清除（优先落地版本）。** + +```text +读取第三问参数，生成七点 S(1200)，初始化逐频道观测和覆盖账本 +调用 /enter，记录官方时间预算 +while 尚有未知频道的站点记录未完成： + 若预算不足：标记未完成，转退出 + 选择仍有未知频道待测的最近站点 s + 在 s 批量测量待查频道（当前测向频道若在其中，优先测） + no_signal：记录该频道在 s 的覆盖证据 + direction：更新该频道 K，加入待定位队列 + near：在 s 清除并依据响应更新状态 + 对本站结束后的待定位队列： + 按当前位置到候选圆心距离选最近频道 + 调用问题二安全选点与问题一清除证书完成其定位子循环 + 清除成功后重新排序；未完成者保留，单轮不无限重试 + 若已清除16个：结束任务 +根据逐频道七点账本标记无源；继续处理尚未清除的已发现频道 +仅在全频道均已清除/有无源证明时标记完成 +调用 /exit；退出响应失败单独记录，不能宣称正常结束 +``` + +**算法3B：在3A之上逐项增加的完整改进规划。** 每次 `direction/near` 更新存在集合 $\mathcal P$，达到16时提前结束未知频道搜索；在各实际测量点更新负观测区域并进行有证书的站点替代；用插入耗时比较“先搜下一站”与“先做某个源”；对候选路线重排；以预计剩余时间选择安全测点，在可清除区域中选择省路位置；定位停滞时按预算调用有限后备。每执行一个动作就用真实响应更新状态，禁止整段盲执行预测的后续动作。 + +```mermaid +flowchart TD + A[进入并读取预算] --> B[更新逐频道证据与完成条件] + B -->|已全清且无遗漏证明完整| X[退出并保存日志] + B -->|预算不足| Y[按未完成退出] + B -->|仍有任务| C[候选覆盖站与定位清除任务] + C --> D[比较短程总耗时并保持覆盖责任] + D --> E[同站批量扫描或执行一次定位清除动作] + E --> F[接收官方响应并验证候选及证书] + F --> B +``` + +第一版和后续规划分别命名，防止把3B尚未实现的负观测跳站、时间型选点和后备算法算进3A的测试成绩。 + +## 11. 计算量与工程实现 + +七点固定账本最多 $7\times20=140$ 个布尔记录。最近站选择检查7个点，每次按至多20个频道统计待测项；16个源的贪心任务队列重排规模很小。固定站路线的开放路径最优排序如需精确解，可使用子集动态规划，规模为 $O(k^2 2^k)$、$k\le7$；但加入观测依赖的定位任务后不再是同一个静态问题。 + +定位计算仍主要消耗在多个候选点、候选源见证点、读数分支的几何裁剪和最小圆计算。假设候选测点 $Q$ 个、读数区间 $B$ 个、外包顶点 $V$ 个，单层保守评估包含 $QB$ 次裁剪和最小圆计算，可表示为 $O(QB[V+T_{\rm MEC}(V)])$；两层分支不能简单称为线性。复用候选集缓存、先粗筛少量入围点，再完整区间验证，能够控制现实计算预算。 + +残余区域若使用 $H$ 个单元，20频道掩码空间为 $O(20H)$，一次频道负观测朴素检查 $O(H)$；可以预计算七锚点的单元覆盖掩码，并通过空间索引限制动态点的更新范围。分辨率只控制证书的保守程度，不得因内存不足删除尚未证实的残余格。 + +| 模块 | 当前事实 | 建议改动 | +| --- | --- | --- | +| `coverage` | 共用49点与逐频道账本 | 新增第三问七点构造；保留第四问网格及其独立证明 | +| `planner.OmnidirectionalLoop` | 发现后立即离站定位 | 把“本站扫频”与“队列服务”拆开，引入第三问策略选项 | +| `belief` | 无信号不裁剪候选 | 增加第三问独立残余覆盖层，避免破坏第四问朝向语义 | +| `geometry/planning`、`planner` | 有安全选点与最小圆证书 | 后续增加最近安全清除点和时间型候选评分 | +| `evaluation` | 浮点累计、固定微秒容差 | 单独兼容官方逐步微秒时钟和自建连续时钟，保留两种原始口径 | +| `protocol` | 串行、幂等、预算退出、JSONL日志 | 延用；增加的动作仍走同一客户端，不能并发测多个频道 | + +实际路径分别位于 [coverage](C:/Users/HelixCopex/code/MATH/src/mcm26b/coverage/__init__.py)、[planner](C:/Users/HelixCopex/code/MATH/src/mcm26b/planner/__init__.py)、[belief](C:/Users/HelixCopex/code/MATH/src/mcm26b/belief/__init__.py)、[evaluation](C:/Users/HelixCopex/code/MATH/src/mcm26b/evaluation/__init__.py)。前两问文档中部分旧路径仍写为根目录 `geometry`，复用时以当前 `src/mcm26b/geometry` 为准。 + +## 12. 已完成的自建配对消融 + +### 12.1 实验口径 + +为验证优先级，新增独立脚本 [benchmark_q3_search.py](C:/Users/HelixCopex/code/MATH/scripts/benchmark_q3_search.py)，只连接进程内 `LocalSimulator`，不连接官方端口、不修改生产策略。数据保存在 [search-ablation](C:/Users/HelixCopex/code/MATH/output/q3/search-ablation/benchmark.json)，同时逐局保存源场景、固定误差场种子、接受动作日志与哈希。 + +共12个场景：源数10和16各一组，每组包含 `random_omni_scene` 种子0、1、2、3、4的5个场景，以及1个源位于1800米边界、接收半径均为1000米的场景。随机生成器径向采样不是圆域面积均匀分布，并特意含近边界源，不将其称为真实场景分布。各变体使用同一局源坐标、接收半径、频道和固定空间误差场；不同位置的合成误差机制不代表官方误差场。边界例包含扇区接缝附近的源。 + +比较四种版本，均沿用现有安全选点与清除内核、舍入裕量0.005°和8次追加检测限额： + +| 版本 | 唯一涉及的搜索与调度变化 | +| --- | --- | +| A0：49点即时定位 | 当前生产基线 | +| A1：七点即时定位 | 只把覆盖点换成七点，仍发现即离站 | +| A2：七点本站批量 | 本站扫频完成后，按最近候选圆心服务队列；当前频道优先 | +| A3：七点全域先扫 | 扫完所有必要覆盖站后，再按最近候选圆心定位；near仍原地清除 | + +A2/A3都包含当前频道优先这一小优化，因此A1与A2之差不是“纯粹只改变一个排序变量”的严格单因素实验。后续应再拆分消融换频顺序。3B的动态残余区域、16个已发现源提前停止搜索、时间型选点、最近安全清除点及后备均未在这组实验启用。 + +### 12.2 全部12个场景结果 + +| 版本 | 全清且正常完成 | 平均虚拟时间 / 秒 | 平均检测数 | 平均移动距离 / 米 | 平均逐局时间降幅 | +| --- | ---: | ---: | ---: | ---: | ---: | +| A0 | 12/12 | 13788.04 | 418.00 | 56183.95 | — | +| A1 | 12/12 | 7476.09 | 100.42 | 34146.70 | 43.25% | +| A2 | 12/12 | 5496.20 | 100.92 | 24177.66 | **58.55%** | +| A3 | 12/12 | 6094.73 | 101.67 | 27164.04 | 53.90% | + +每个版本共清除156个源，48局合计624个源全部清除，无失败清除、无错误缺席判定、无定位异常。A2相对A0的逐局降幅范围为37.50%至70.84%。降幅按 $\frac1n\sum_i(1-T_{A2,i}/T_{A0,i})$ 计算，不能与两个均值之比混称同一个指标。 + +另以保存的自建场景真值独立复核48局动作日志，逐步检查正观测后的候选保留真源、清除证书及实际清除距离、全清集合、计时、检测数、退出响应与日志哈希，全部通过，见[证据复核结果](C:/Users/HelixCopex/code/MATH/output/q3/search-ablation/evidence-audit.json)。这些真值只用于离线验收，不进入策略。 + +| 源数（每组6场景） | A0平均时间 / 秒 | A1平均时间 / 秒 | A2平均时间 / 秒 | A3平均时间 / 秒 | +| --- | ---: | ---: | ---: | ---: | +| 10 | 15516.58 | 6313.47 | **4836.11** | 5467.38 | +| 16 | 12059.50 | 8638.71 | **6156.28** | 6722.08 | + +10源时，未知频道的无源证明开销较大，所以七点替换收益明显；16源时，可通过清除数量上界提前停止，原网格未必扫完，但批量调度仍显著减少移动。A1与A2检测数相近，A2平均移动距离进一步下降，表明减少往返比单纯少测一次更有价值。这组自建证据支持优先实现A2，而非先投入复杂概率图、强化学习或全局非线性优化。 + +四版本平均本地计算墙钟约1.7至1.8秒/局，记录在数据中；它不含官方网络、真实程序截止或官方UI开销，不能当作新方案官方现实耗时。原官方动作日志只能验证旧路径上的响应，不能用它推断新测点的读数。只有在官方新演练执行新策略后，才能报告官方提速。 + +### 12.3 复现 + +```powershell +.venv/Scripts/python.exe scripts/benchmark_q3_search.py --seeds 0,1,2,3,4 +``` + +也可使用 `uv run python` 调用同一脚本。输出包含原始逐局数据，失败不会从汇总中剔除。当前实验是小规模方案筛选，不能证明所有合法场景、所有固定误差场或不同环半径下的性能。 + +## 13. 分阶段改进与验收计划 + +| 阶段 | 交付 | 必须通过的验收 | +| --- | --- | --- | +| I：七点＋本站批量 | 将A2接入第三问CLI选项，保留A0可切换；原始日志格式兼容 | 七点连续覆盖证明与坐标误差预算；10/16源及边界例全清；第四问覆盖策略未被改动 | +| II：存在计数与扫频次序 | $|\mathcal P|=16$ 提前停止未知频道扫描；同站频道优先独立消融 | 已发现数、已清除数不混淆；发现10个不能停；clear不改变测向频道 | +| III：残余覆盖与顺路观测 | 保守单元账本、负观测复用、有证书跳站 | 边界及单元接缝不漏；未知频道各有独立覆盖责任；启发式停滞自动恢复七点 | +| IV：时间型局部动作 | 最近安全清除点、短程任务预演、插入排序 | 实际提交点满足全部外包顶点约束；near和跨0°读数正确；采样评分不冒充严格上界 | +| V：定位停滞与预算后备 | 有界区域有限清除覆盖，明确上限与退出 | 清除格子覆盖全部候选；格数/两种时间预算不足均记未完成；故障与失败可回放 | + +每个阶段都在相同场景和同一固定误差场上进行配对比较。建议将种子0—4保留为本次开发集；最终验证另生成独立种子100—199，并分别覆盖10至16个源、接收半径1000和1500米、边界源、团簇源、同站near、接近共线读数、误差恰在±1°及空间相关误差场。所有超时、矛盾和未全清样例进入结果表，不允许只报成功局。 + +主要指标为全清且正常退出比例、平均/中位/P95/最大虚拟总时间、移动长度、检测数、换频数、清除失败数、证明无源的成本；同时报告最后清除时刻、现实计算时间与总请求数。小样本不确定性用逐局配对差分及其范围表达，增加样本后可在声明抽样假设的前提下给出区间估计；不从当前12例推出总体成功率为100%。 + +官方验收继续使用 socket 接口，逐条保存请求响应，最后保存官方结果及加密日志；优先使用官方支持的同案例复现功能进行配对，如果无法复现同一案例，就分别报告案例差异，不将两次随机局的时间差当成纯算法收益。本轮只完成方案研究与自建实验，没有再次启动官方演练。 + +## 14. 结论与实现边界 + +第三问首先应把覆盖责任从49点缩减为已证明足够的七点，并将覆盖站内扫频和离站定位拆开。该改进直接针对官方日志中的主要开销，在保持几何定位方法不变时，已经得到12个自建场景的配对支持。推荐先落地A2，再独立验证存在数量上界、残余覆盖和时间型测点/清除点优化。 + +初稿形成时，七点与三种调度变体存在于离线消融脚本，官方仅验证A0；随后A2已通过下述一次官方演练。生产 `src/mcm26b` 默认策略仍未修改，A2由独立运行脚本调用。3B给出了可实现的进一步规划，但没有将其预期收益写成已测结果。固定覆盖、观测集合和清除证书负责可靠性；候选评分、任务排序和半径调参负责效率，二者的保证范围分别陈述。 + +## 15. 补充：A2官方演练已通过 + +在方案研究之后，用户启动新的问题3演练，于2026-09-11通过2026端口实际执行A2。案例 `J4ER-Y9EP-Q379-UPFA` 的官方源数为12，12个全部清除，109次检测、12次清除无失败，现实耗时3.406秒，总虚拟耗时5232.132109秒（1小时27分12秒），移动22645.661米。其余8个频道各有完整七点无信号记录，最终正常退出。 + +123个请求响应已严格离线回放，清除证书和官方微秒计时全部通过复核。原始数据、官方产物、运行代码哈希及复现入口见[本局验证报告](C:/Users/HelixCopex/code/MATH/output/q3/practice/20260911-seven-batch-01/report.md)。因此A2现已有自建配对实验及一个官方案例的有效性证据。 + +相较之前A0官方10源案例的16217.454814秒，本局虚拟时间少67.74%，但案例和源数不同，不能把该差异称为严格算法提速率；第12节的58.55%仍仅指12个自建场景的配对平均结果。3B的进一步改进尚未启用。 + +## 参考文献 + +1. 全国大学生数学建模竞赛组委会. 2026年高教社杯全国大学生数学建模竞赛B题：无线电干扰源的快速自动定位与清除[Z]. 2026. [题面](C:/Users/HelixCopex/code/MATH/issue/B题.pdf)；模拟器配套材料《附件2：模拟器通信接口说明及编程指南》[本地文件](C:/Users/HelixCopex/code/MATH/issue/附件/附件2.docx)。 +2. 本项目. 问题一：有界测向误差下定位区域的直径与圆覆盖；问题二：具有接收保证的第二检测点选择[Z]. 2026. [algo-1](C:/Users/HelixCopex/code/MATH/docs/algo-1.md)、[algo-2](C:/Users/HelixCopex/code/MATH/docs/algo-2.md)。 +3. BAYRAM H, VANDER HOOK J, ISLER V. Gathering Bearing Data for Target Localization[J]. IEEE Robotics and Automation Letters, 2016, 1(1): 369–374. DOI: 10.1109/LRA.2016.2521387. [作者所在大学的研究记录](https://experts.umn.edu/en/publications/gathering-bearing-data-for-target-localization-6/)。核对题目、作者、页码及移动与测量联合代价；未套用其GDOP近似比。 +4. OLOFSSON J, HENDEBY G, LAUKNES T R, JOHANSEN T A. Multi-Agent Informed Path Planning Using the Probability Hypothesis Density[J]. Autonomous Robots, 2020. [作者公开稿](https://torarnj.folk.ntnu.no/AURO2020a.pdf)，第1—2节。用于未观测区域与预算路径的建模对照。 +5. PERERA A, TRAN V P, ANAVATTI S, KASMARIK K, GARRATT M. Radio Source Localization using Sparse Signal Measurements from Uncrewed Ground Vehicles[EB/OL]. arXiv:2312.03493, 2023. [原文入口](https://arxiv.org/abs/2312.03493)。用于稀疏覆盖与实验设计的对照，RSSI估计器未迁移。 +6. ATANASOV N A, LE NY J, PAPPAS G J. Distributed Algorithms for Stochastic Source Seeking with Mobile Robot Networks: Technical Report[EB/OL]. arXiv:1402.0051v2, 2014. [原文入口](https://arxiv.org/abs/1402.0051)。用于说明场强梯度和测量模型假设的适用边界，不引用其结论证明本算法收敛。 + +在线来源核对日期：2026-09-11。本文的七点构造、覆盖界和具体调度规划来自对题设参数的推导与本项目实验，不宣称一般几何和路径规划思想在文献中首次出现。 diff --git a/output/q3/practice/20260911-port2026/actions.csv b/output/q3/practice/20260911-port2026/actions.csv new file mode 100644 index 0000000..9fa746d --- /dev/null +++ b/output/q3/practice/20260911-port2026/actions.csv @@ -0,0 +1,553 @@ +index,path,request_id,channel,x,y,result,svd_deg,distance_m,move_us,switch_s,action_s,recomputed_us,recorded_s,gap_us +0,/enter,6a0e3e473e4f-0001,,0.0,0.0,,,0.0,0,0,0,0,0,0 +1,/measure,6a0e3e473e4f-0002,1,0.0,0.0,no_signal,,0.0,0,0,5,5000000,5,0 +2,/measure,6a0e3e473e4f-0003,2,0.0,0.0,direction,141.21,0.0,0,1,5,11000000,11,0 +3,/measure,6a0e3e473e4f-0004,2,-519.8219235407033,711.5286774266888,direction,291.08,881.1855031683906,176237101,0,5,192237101,192.237101,0 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b/output/q3/practice/20260911-port2026/practice-p3-4317927797384597197-DHFK-PHD2-SR2P-FXK9.result.json @@ -0,0 +1 @@ +{"version":2,"problem_no":3,"practice_run_no":4317927797384597197,"case_code":"DHFK-PHD2-SR2P-FXK9","package_sha256":"2b3c3b9359e0a92f04a845935d79c6f989bbe6b504bfa51abe6b841485b9f96a","window_started_at_utc":"2026-09-10T18:42:11.431Z","ended_at_utc":"2026-09-10T18:43:49.91Z","jammer_count":10,"omnidirectional_jammer_count":10,"directional_jammer_count":0} \ No newline at end of file diff --git a/output/q3/practice/20260911-port2026/regression.txt b/output/q3/practice/20260911-port2026/regression.txt new file mode 100644 index 0000000..dc5eaf6 --- /dev/null +++ b/output/q3/practice/20260911-port2026/regression.txt @@ -0,0 +1,2 @@ +.............................................. [100%] +46 passed in 9.70s diff --git a/output/q3/practice/20260911-port2026/replay_summary.json b/output/q3/practice/20260911-port2026/replay_summary.json new file mode 100644 index 0000000..048282a --- /dev/null +++ b/output/q3/practice/20260911-port2026/replay_summary.json @@ -0,0 +1,110 @@ +{ + "completed": true, + "stop_reason": "all_resolved", + "exit_reason": "user_exit", + "virtual_time_s": 16217.455, + "cleared_channels": [ + 2, + 4, + 7, + 8, + 9, + 13, + 16, + 17, + 18, + 19 + ], + "absent_channels": [ + 1, + 3, + 5, + 6, + 10, + 11, + 12, + 14, + 15, + 20 + ], + "unresolved_channels": [], + "measures": 540, + "clears": 10, + "clear_success": 10, + "total_requests": 550, + "move_distance_m": 64737.3, + "anomalies": [], + "virtual_recompute_mismatches": 541, + "channel_status": { + "1": { + "status": "absent" + }, + "2": { + "status": "cleared", + "posterior_radius_m": 9.999 + }, + "3": { + "status": "absent" + }, + "4": { + "status": "cleared", + "posterior_radius_m": 10.549 + }, + "5": { + "status": "absent" + }, + "6": { + "status": "absent" + }, + "7": { + "status": "cleared", + "posterior_radius_m": 9.886 + }, + "8": { + "status": "cleared", + "posterior_radius_m": 8.978 + }, + "9": { + "status": "cleared", + "posterior_radius_m": 5.001 + }, + "10": { + "status": "absent" + }, + "11": { + "status": "absent" + }, + "12": { + "status": "absent" + }, + "13": { + "status": "cleared", + "posterior_radius_m": 10.408 + }, + "14": { + "status": "absent" + }, + "15": { + "status": "absent" + }, + "16": { + "status": "cleared", + "posterior_radius_m": 10.665 + }, + "17": { + "status": "cleared", + "posterior_radius_m": 9.636 + }, + "18": { + "status": "cleared", + "posterior_radius_m": 12.394 + }, + "19": { + "status": "cleared", + "posterior_radius_m": 17.112 + }, + "20": { + "status": "absent" + } + } +} diff --git a/output/q3/practice/20260911-port2026/report.md b/output/q3/practice/20260911-port2026/report.md new file mode 100644 index 0000000..2d308c6 --- /dev/null +++ b/output/q3/practice/20260911-port2026/report.md @@ -0,0 +1,75 @@ +# 第三问官方 Simulator 演练验证 + +结论：现有第三问方案在本次官方演练中有效，10 个干扰源全部清除，正常退出。该结论适用于本次案例，不代表已验证所有案例，也不代表虚拟耗时最优。 + +## 本局与运行方式 + +- 本地日期：2026-09-11（Asia/Shanghai）。 +- 官方案例编码：`DHFK-PHD2-SR2P-FXK9`；演练编号：`4317927797384597197`。 +- 官方结果：问题 3，10 个全向源，0 个定向源。 +- 使用用户已启动的演练，通过 `http://127.0.0.1:2026` 的 HTTP/TCP socket 串行调用 `/enter`、`/measure`、`/clear`、`/exit`；未使用 computer use。 +- 运行代码版本：`846b45e42018689b2568bc0b089f72d53113b519`，运行前 Git 工作区干净。采用现有 `OmnidirectionalLoop` 和 CLI 默认参数，示向度舍入裕量为 0.005°，未修改策略。 +- 队号取自项目既有官方演练记录，当前 `/enter` 接受，确认匹配。 +- 官方案例源数仅在退出后读取，用于验收；运行时策略仅使用协议观测。 + +```powershell +.venv/Scripts/python.exe -m mcm26b.cli run --robot-id 202608023016 --problem 3 --base-url http://127.0.0.1:2026 --log output/q3/practice/20260911-port2026/session.jsonl +``` + +## 实测结果 + +| 指标 | 结果 | +| --- | ---: | +| 官方源数 / 成功清除数 | 10 / 10 | +| 检测次数 | 540 | +| 清除尝试 / 失败 | 10 / 0 | +| 接受的 HTTP 请求数（含进入、退出） | 552 | +| 现实运行时间（服务器时间戳差） | 7.629 秒 | +| 虚拟总耗时 | 16217.454814 秒（4小时30分17.455秒） | +| 移动距离 | 64737.274 米 | +| 移动耗时 | 12947.454814 秒 | +| 检测耗时 | 2700 秒 | +| 换频道耗时 | 520 秒 | +| 清除耗时 | 50 秒 | +| 重试、拒绝、定位/清除异常 | 0 | +| 结束原因 | `all_resolved` / `user_exit` | + +清除频道：2、4、7、8、9、13、16、17、18、19。其余 1、3、5、6、10、11、12、14、15、20 频道，各自均有完整的 49 个覆盖点无信号记录；不存在未解决频道。 + +最后一个源在虚拟时刻 8454.332399 秒清除。此后仍执行覆盖证明，耗时 7763.122415 秒，占总虚拟耗时约 47.87%。完整网格扫描和移动是后续效率优化的重点；提前发现 10 个源本身不能作为停止依据。 + +## 验证证据与计时问题 + +离线审计的 14 项检查全部通过：官方问题与源数、官方日志包 SHA-256、进入退出、响应所属时间窗口、请求 ID 唯一性、无重试拒绝、全清除、每次清除成功、原汇总完成状态、无源频道覆盖、逐步微秒计时、双时间预算、完整动作回放、清除证书。 + +严格回放只使用录制的响应，逐次比较新生成的请求路径及全部动作字段（仅忽略随机 request_id），重现全部 552 个请求。重算的 10 个清除证书均满足候选外包半径小于证书限值，限值小于 20 米。 + +原始 `summary.json` 中 `virtual_recompute_mismatches=541` 为计时精度误报：项目现有 `evaluation.recompute_virtual_time` 累计未经量化的浮点秒数，并使用固定 1 微秒累计容差；官方附件2第4.1节规定模拟器内部按微秒累计。本次按每次移动耗时四舍五入为整数微秒后，552 个官方时刻全部精确匹配，偏差数为 0。单次未经量化的耗时最大偏差为 0.493106 微秒，最终累计差为 -1.215829 微秒。 + +审计脚本已正确复算本局，但未修改现有生产计时复算函数，因此其原始误报仍保留在 `summary.json` 和 `replay_summary.json` 中。此问题不影响本局实际动作、清除成功或退出；若用于后续自动验收，应统一项目复算精度。 + +相关既有回归测试：第三问闭环、协议客户端、计时规则及演练记录验证，共 **46 项通过**，见 `regression.txt`。 + +## 保存文件与复核 + +| 文件 | 用途 | +| --- | --- | +| `session.jsonl` | 逐条原始请求、官方响应、现实时间及尝试记录 | +| `summary.json` | 本次 CLI 原始输出，保留原始计时误报 | +| `actions.csv` | 552 个接受动作、坐标、频道、读数、耗时及逐步微秒复算 | +| `verification.json` | 独立验收结果、覆盖证明、证书、计时分解 | +| `replay_summary.json` | 现有策略对录制响应的严格离线回放结果 | +| `*.result.json` | 官方演练案例元数据与源数 | +| `*.jlog`、`*.psum` | 原样复制的官方加密产物，未解密 | +| `manifest.json` | 保存文件的字节数与 SHA-256 | +| `regression.txt` | 46 项相关测试结果 | + +官方 `.jlog` 的 SHA-256 为 `2b3c3b9359e0a92f04a845935d79c6f989bbe6b504bfa51abe6b841485b9f96a`，与官方 `.result.json` 中 `package_sha256` 一致。全清除结论来自 10 个不同频道的官方成功响应与官方总源数交叉核对；未解密加密统计，也未声称读取官方评分。 + +在项目根目录可离线复核，无需启动模拟器： + +```powershell +.venv/Scripts/python.exe scripts/verify_q3_practice.py output/q3/practice/20260911-port2026 +``` + +复核只重写派生审计文件，保留原始会话、原始汇总及官方产物。 diff --git a/output/q3/practice/20260911-port2026/session.jsonl 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z=&IeKZOd&%hulQ3SBj`j)9c|0$qc2UY*yAW9y1g@5$S*uNTG_CUsLT|YMUnfAfh*tFBzH(yx$mlap156@&hW?#2F`F7-Im3NnZV4o_>7GAV?&WyrqV9|bH%Y&Ryn7DJ}cdm#%aG~CwmirXm|J{pq zZv5w4)*ilwKX^*B54?H(c5VBCGmnY8mftBHWiQ{h^7J)>mFGQj(?E+yzu+&|9Yoo9rey^r{0M($F{%p;Dt|Lw{Y+5 zua>X>-SL^{mkwPq{oDb~25?=P;zJFc=KD;%0+1&ZYzrB6`$s69g`b!r-cE=oW`PTnl zdJtP|&MW=bEuZ}1-ft~Ca%%6Ii;-rd_{jQ4zrNu6%aNTQ&YF1S+>h@)GPnBBDfO;* zUcPzT;;j@`HwxZ=Ve)$-PrX%le6(#j_vx^X6(p zFHCMaG<&i~Jv2{#QM}{Q`)>S70qlMA+~s!ct>asEC*NE;d+$ekAJXRT+=*?Oce1`hNXYH?f$0@pVylItJ~(Um9dkrTzzKRn(VVL9G-R01#{7N z&ZWM#`JI2)3S;kIH)t=o_t9q;{rvq87vDbP`UBhEczWfY7k|08xn$!{PanT$|K!DM zc5}C`p8o#J)!5+~V?R6f)LS2rdk^Mz{$#^W`^Br*97bez)3y6ji$9yS=k}TMx^LhA z*>j7GKVP-%5PbBH=e*UJ@%2v@8JlkT=+y@}5bZl3w_>I2hL0<#Bs zwSCbeC%(LK?ek0SxPQf~4_yB6{NwNb_R5=9-hG+<>O(2##kXE3UX4EUB zbz=VG4szdJ>*j9SePZk48$bS7*>G^lk59*b6npaMobP`2qYw8_ZceOVF8$yu9{c76 zx88TcUAW`!b+7H+@SFXw_cMRo{!i~Nd0*~=Lj6CVA3NhrwEukKd(*eiI worst[0]: + worst = (d, p) + return {"ring_radius_m": RING_RADIUS_M, "points": points, + "analytic_cover_radius_m": analytic, "reception_margin_m": field.r_eff_min_m-analytic, + "sampled_max_distance_m": worst[0], "sampled_worst_point": worst[1], + "samples": 181*721, + "passed": worst[0] <= analytic+1e-8 and analytic < field.r_eff_min_m, + "note": "Grid samples check the derivation; the sector proof establishes continuous coverage."} + + +def main(): + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--seeds", default="0,1,2,3,4") + parser.add_argument("--out", type=Path, default=ROOT/"output/q3/search-ablation") + args = parser.parse_args() + args.out.mkdir(parents=True, exist_ok=True) + rows = [] + for count in (10, 16): + for seed in [int(s) for s in args.seeds.split(",")]: + rows.extend(run_case(f"random-{count}-seed{seed}", random_omni_scene(seed, count), + 20260910+seed, args.out)) + # Sources on the exact outer boundary at sector seams; minimum receiving radius. + edge = [Source(c+1, 1800*math.cos(math.pi/6+2*math.pi*c/count), + 1800*math.sin(math.pi/6+2*math.pi*c/count), 1000) for c in range(count)] + rows.extend(run_case(f"boundary-{count}", edge, 20260910, args.out)) + aggregates = {} + for label in VARIANTS: + part = [r for r in rows if r["variant"] == label] + baseline = {r["case"]: r for r in rows if r["variant"] == "grid49_immediate"} + savings = [1-r["virtual_time_s"]/baseline[r["case"]]["virtual_time_s"] for r in part] + aggregates[label] = { + "runs": len(part), "all_cleared_runs": sum(r["all_cleared"] for r in part), + "valid_runs": sum(r["all_cleared"] and r["completed"] and r["correct_absence"] + and r["normal_exit"] and not r["anomalies"] for r in part), + "mean_virtual_s": mean(r["virtual_time_s"] for r in part), + "median_virtual_s": median(r["virtual_time_s"] for r in part), + "max_virtual_s": max(r["virtual_time_s"] for r in part), + "mean_measures": mean(r["measures"] for r in part), + "mean_distance_m": mean(r["distance_m"] for r in part), + "mean_compute_wall_s": mean(r["compute_wall_s"] for r in part), + "mean_paired_time_reduction": mean(savings), + "min_paired_time_reduction": min(savings), + "max_paired_time_reduction": max(savings), + "failed_clears": sum(r["failed_clears"] for r in part), + } + result = {"source": "local_simulator_only", "production_algorithm_modified": False, + "seeds": args.seeds, "config": asdict(ProblemConfig()), + "geometry": geometry_check(), "aggregates": aggregates, "runs": rows, + "limitations": "Same scene and fixed per-position error field for each variant; synthetic data, not an official improvement estimate. Only search/scheduling is changed; no posterior or localizer redesign."} + (args.out/"benchmark.json").write_text(json.dumps(result, ensure_ascii=False, indent=2), encoding="utf-8") + print(json.dumps(aggregates, ensure_ascii=False, indent=2)) + return 0 if result["geometry"]["passed"] and all(a["valid_runs"] == a["runs"] for a in aggregates.values()) else 1 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/run_q3_seven_practice.py b/scripts/run_q3_seven_practice.py new file mode 100644 index 0000000..f48ce6d --- /dev/null +++ b/scripts/run_q3_seven_practice.py @@ -0,0 +1,53 @@ +"""Run SevenBatch on an already authorized official Q3 practice session. + +Does not start a practice/formal test. All actions use the documented HTTP API. +""" +import argparse +from dataclasses import asdict, replace +from datetime import datetime +import hashlib +import json +from pathlib import Path +import time + +from benchmark_q3_search import SevenBatch, seven_points +from mcm26b.config import ProblemConfig +from mcm26b.protocol.client import SimulatorClient +from mcm26b.protocol.log import SessionLog + + +def main(): + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--robot-id", required=True) + parser.add_argument("--practice-confirmed", action="store_true", required=True) + parser.add_argument("--base-url", default="http://127.0.0.1:2026") + parser.add_argument("--output", type=Path, required=True) + args = parser.parse_args() + args.output.mkdir(parents=True, exist_ok=False) + config = ProblemConfig() + config = replace(config, session=replace(config.session, base_url=args.base_url)) + root = Path(__file__).resolve().parents[1] + paths = [Path(__file__).resolve(), root / "scripts/benchmark_q3_search.py", + *sorted((root / "src/mcm26b").rglob("*.py"))] + metadata = {"source": "official_practice", "problem": 3, + "strategy": "seven_batch", "started_local": datetime.now().astimezone().isoformat(), + "config": asdict(config), "coverage_points": seven_points(), + "source_sha256": {str(p.relative_to(root)): hashlib.sha256(p.read_bytes()).hexdigest() + for p in paths}} + def save(name, value): + (args.output / name).write_text(json.dumps(value, ensure_ascii=False, indent=2, + allow_nan=False) + "\n", encoding="utf-8") + save("run_metadata.json", metadata) + log = SessionLog(path=args.output / "session.jsonl") + client = SimulatorClient(args.robot_id, config=config, log=log) + started = time.perf_counter() + summary = SevenBatch(client, config).run() + summary.update(robot_id=args.robot_id, strategy="seven_batch", + real_wall_s=time.perf_counter()-started) + save("summary.json", summary) + print(json.dumps(summary, ensure_ascii=False, indent=2)) + return 0 if summary["completed"] and summary["exit_reason"] == "user_exit" else 1 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/verify_q3_practice.py b/scripts/verify_q3_practice.py new file mode 100644 index 0000000..1ae2cfd --- /dev/null +++ b/scripts/verify_q3_practice.py @@ -0,0 +1,237 @@ +"""Offline audit of an official Q3 run; never connects to the simulator. + +Usage: python scripts/verify_q3_practice.py output/q3/practice/20260911-port2026 +Preserves session.jsonl and summary.json; writes derived audit artifacts only. +""" + +from __future__ import annotations + +import argparse +import csv +from dataclasses import asdict +from datetime import datetime +import hashlib +import json +import math +from pathlib import Path +from urllib.parse import urlsplit + +from benchmark_q3_search import SevenBatch, seven_points +from mcm26b.config import ProblemConfig +from mcm26b.coverage import coverage_points +from mcm26b.evaluation import recompute_virtual_time +from mcm26b.planner import OmnidirectionalLoop +from mcm26b.protocol.client import SimulatorClient +from mcm26b.sim.playback import PlaybackTransport + + +class StrictPlayback(PlaybackTransport): + """Check complete action content, not merely the sequence of API paths.""" + + def post(self, url, body, headers, timeout): + if self.index >= len(self.events): + raise AssertionError("Replay attempted an extra action") + expected = self.events[self.index] + actual_request = json.loads(body) + without_id = lambda value: {k: v for k, v in value.items() if k != "request_id"} + if (urlsplit(url).path != expected["path"] or + without_id(actual_request) != without_id(expected["request"])): + raise AssertionError(f"Replay action differs at index {self.index}") + return super().post(url, body, headers, timeout) + + +class AuditMixin: + def __init__(self, client, config): + super().__init__(client, config) + self.certificates = [] + + def _attempt_clear(self, channel, target, cert): + vertices = self.belief.candidate_set(channel).polygon + self.certificates.append({**asdict(cert), "submitted_position": target, + "submitted_max_vertex_distance_m": + max(math.dist(target, v) for v in vertices)}) + return super()._attempt_clear(channel, target, cert) + + +class AuditedLoop(AuditMixin, OmnidirectionalLoop): + pass + + +class AuditedSevenBatch(AuditMixin, SevenBatch): + pass + + +def save_json(path, value): + path.write_text(json.dumps(value, ensure_ascii=False, indent=2, + allow_nan=False) + "\n", encoding="utf-8") + + +def audit(folder: Path) -> dict: + records = [json.loads(line) for line in + (folder / "session.jsonl").read_text(encoding="utf-8").splitlines()] + events = [e for e in records if e.get("event") == "accepted"] + original = json.loads((folder / "summary.json").read_text(encoding="utf-8-sig")) + strategy = original.get("strategy", "grid49_immediate") + if strategy not in ("grid49_immediate", "seven_batch"): + raise ValueError(f"Unsupported strategy: {strategy}") + official_paths = list(folder.glob("*.result.json")) + if len(official_paths) != 1 or not events: + raise ValueError("Expected one official result and nonempty session evidence") + official_path = official_paths[0] + official = json.loads(official_path.read_text(encoding="utf-8")) + package = official_path.with_name(official_path.name.replace(".result.json", ".jlog")) + + checks = {} + checks["official_problem_3_all_omnidirectional"] = ( + official["problem_no"] == 3 and official["directional_jammer_count"] == 0 + and 10 <= official["jammer_count"] <= 16 + and official["omnidirectional_jammer_count"] == official["jammer_count"]) + checks["official_package_sha256_matches"] = ( + hashlib.sha256(package.read_bytes()).hexdigest() == official["package_sha256"]) + checks["normal_enter_and_exit"] = ( + events[0]["path"] == "/enter" and events[-1]["path"] == "/exit" + and events[-1]["response"].get("exit_reason") == "user_exit") + start_ms = datetime.fromisoformat(official["window_started_at_utc"]).timestamp() * 1000 + end_ms = datetime.fromisoformat(official["ended_at_utc"]).timestamp() * 1000 + checks["responses_within_official_run_window"] = all( + start_ms <= e["response"]["real_timestamp_ms"] <= end_ms + 1 for e in events) + ids = [e["request"]["request_id"] for e in events] + checks["unique_accepted_request_ids"] = len(ids) == len(set(ids)) + checks["no_rejections_or_retries"] = ( + len(records) == 2 * len(events) + and all(e.get("attempts") == 1 for e in events) + and all(records[2*i].get("event") == "attempt" + and records[2*i]["request"] == e["request"] + and records[2*i+1] == e for i, e in enumerate(events))) + clears = [e for e in events if e["path"] == "/clear"] + successes = [e for e in clears if e["response"].get("clear_result") == "success"] + cleared = sorted({e["request"]["channel"] for e in successes}) + checks["all_official_sources_cleared"] = len(cleared) == official["jammer_count"] + checks["every_clear_succeeded_once"] = len(clears) == len(successes) == len(cleared) + checks["original_summary_completed"] = ( + original["completed"] and original["cleared_channels"] == cleared + and original["unresolved_channels"] == [] and original["anomalies"] == []) + + grid = set(seven_points() if strategy == "seven_batch" else coverage_points()) + absent_coverage = {} + for channel in sorted(set(range(1, 21)) - set(cleared)): + channel_events = [e for e in events if e["path"] == "/measure" + and e["request"]["channel"] == channel] + points = {(e["request"]["position"]["x"], e["request"]["position"]["y"]) + for e in channel_events if e["response"]["measure_result"] == "no_signal"} + absent_coverage[str(channel)] = { + "grid_points_measured": len(points & grid), "required_grid_points": len(grid), + "all_no_signal": all(e["response"]["measure_result"] == "no_signal" + for e in channel_events), + "complete": grid <= points, + } + checks["absent_channels_fully_covered"] = all( + item["complete"] and item["all_no_signal"] for item in absent_coverage.values()) + + # Official attachment 2 section 4.1: accumulate virtual time in microseconds. + # Round each move to the nearest microsecond, then add integer action costs. + position, channel, virtual_us = (0.0, 0.0), 1, 0 + distance_total, switch_total, move_total_us = 0.0, 0, 0 + rows = [] + previous_recorded = 0.0 + max_local_gap = 0.0 + for i, event in enumerate(events): + request, response, path = event["request"], event["response"], event["path"] + distance, switches, action_s = 0.0, 0, 0 + if path in ("/measure", "/clear"): + target = (request["position"]["x"], request["position"]["y"]) + distance = math.dist(position, target) + position = target + if path == "/measure": + switches = int(channel != request["channel"]) + channel = request["channel"] + action_s = 5 + else: + action_s = 5 if response["clear_result"] == "success" else 3 + move_us = round(distance / 5 * 1_000_000) + virtual_us += move_us + (switches + action_s) * 1_000_000 + distance_total += distance + switch_total += switches + move_total_us += move_us + recorded = response["virtual_time_s"] + gap_us = round(recorded * 1_000_000) - virtual_us + max_local_gap = max(max_local_gap, + abs(recorded - previous_recorded - distance/5 - switches - action_s)) + previous_recorded = recorded + rows.append({"index": i, "path": path, "request_id": request["request_id"], + "channel": request.get("channel", ""), "x": position[0], "y": position[1], + "result": response.get("measure_result", response.get("clear_result", "")), + "svd_deg": response.get("svd_deg", ""), "distance_m": distance, + "move_us": move_us, "switch_s": switches, "action_s": action_s, + "recomputed_us": virtual_us, "recorded_s": recorded, "gap_us": gap_us}) + checks["all_timestamps_match_microsecond_recomputation"] = all(r["gap_us"] == 0 for r in rows) + real_s = (events[-1]["response"]["real_timestamp_ms"] - + events[0]["response"]["real_timestamp_ms"]) / 1000 + checks["within_real_and_virtual_limits"] = ( + real_s < events[0]["response"]["remaining_real_duration_s"] + and virtual_us / 1_000_000 < events[0]["response"]["max_virtual_duration_s"]) + + # Exact action replay independently checks decisions using only recorded responses. + transport = StrictPlayback(events) + config = ProblemConfig() + client = SimulatorClient(original["robot_id"], transport=transport, config=config, + clock=lambda: 0.0) + loop = (AuditedSevenBatch if strategy == "seven_batch" else AuditedLoop)(client, config) + replay_summary = loop.run() + checks["deterministic_action_replay"] = ( + transport.index == len(events) and replay_summary["completed"] + and all(replay_summary[k] == original[k] for k in + ("stop_reason", "cleared_channels", "absent_channels", "measures", "clears"))) + checks["all_clear_certificates_valid"] = ( + len(loop.certificates) == len(clears) + and all(c["certified"] and c["radius_m"] <= c["limit_m"] < 20 + and c["submitted_max_vertex_distance_m"] <= c["limit_m"] + for c in loop.certificates)) + raw_timing = recompute_virtual_time(events) + report = { + "passed": all(checks.values()), "source": "official_practice", "strategy": strategy, + "case_code": official["case_code"], "checks": checks, + "official_jammer_count": official["jammer_count"], "cleared_channels": cleared, + "absent_channel_coverage": absent_coverage, + "accepted_requests_including_enter_exit": len(events), + "measures": len([e for e in events if e["path"] == "/measure"]), + "clear_attempts": len(clears), "clear_successes": len(successes), + "real_elapsed_server_s": real_s, + "real_elapsed_local_s": events[-1]["logged_at_unix_s"] - events[0]["logged_at_unix_s"], + "virtual_time_s": virtual_us / 1_000_000, + "last_clear_virtual_time_s": successes[-1]["response"]["virtual_time_s"], + "move_distance_m": distance_total, "move_time_s": move_total_us / 1_000_000, + "switch_time_s": switch_total, + "measurement_time_s": sum(r["action_s"] for r in rows if r["path"] == "/measure"), + "clear_time_s": sum(r["action_s"] for r in rows if r["path"] == "/clear"), + "timing_audit": { + "original_unquantized_mismatch_count": len(raw_timing["mismatches"]), + "original_unquantized_final_gap_s": previous_recorded - raw_timing["final_virtual_time_s"], + "max_single_action_unquantized_gap_s": max_local_gap, + "microsecond_mismatch_count": sum(r["gap_us"] != 0 for r in rows), + "explanation": "原复算累计未量化浮点耗时；按动作移动耗时取最近整数微秒后，所有官方时刻完全一致。", + }, + "clear_certificates": loop.certificates, + "limits": "仅验证当前官方演练案例；不证明所有案例或时间最优性。官方加密日志保持原样，未解密。", + } + with (folder / "actions.csv").open("w", encoding="utf-8-sig", newline="") as handle: + writer = csv.DictWriter(handle, fieldnames=list(rows[0])) + writer.writeheader() + writer.writerows(rows) + save_json(folder / "verification.json", report) + save_json(folder / "replay_summary.json", replay_summary) + manifest = {p.name: {"bytes": p.stat().st_size, + "sha256": hashlib.sha256(p.read_bytes()).hexdigest()} + for p in sorted(folder.iterdir()) if p.is_file() and p.name != "manifest.json"} + save_json(folder / "manifest.json", manifest) + return report + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("folder", type=Path) + args = parser.parse_args() + result = audit(args.folder) + print(json.dumps({"passed": result["passed"], "case_code": result["case_code"], + "checks": result["checks"]}, ensure_ascii=False, indent=2)) + raise SystemExit(0 if result["passed"] else 1)