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研究命题（00-plan）：验证并打磨《围猎》联机纯音频体验——不是逻辑能跑通， 而是真人玩起来是什么体验、愿不愿意再来一局。 设施 web/harness/hunt-sim/（可复用，零依赖）： - arena.mjs 编排器：起真实服务器（随机端口+临时数据目录隔离），10 个拟人客户端 经真实 WS 同时在线，错峰组队、真实时长对局、局间状态跨轮维护 - sim-client.mjs：game.js 行为移植（协议+手势路由+R1-R8 音频调度逐字节对齐）， 产出「玩家耳朵听到什么」的感知时间线（语音全文/loop 方位音量档/喊话/震动） - brain.mjs：人设大脑——察觉延迟/前后判读（以真值为条件的正确率模型）/掩蔽放大/ 冷却乱滑/技能囤积/呼喊倾向/分心断网，全部随机判定用按实体 id 哈希的独立抽签 （mulberry32 流会被刷怪座位轮转结构带偏，实测造成系统性镜像反转，已证伪） - recorder.mjs：每人每局 events.jsonl 全量 + percept.md 感知转写 + 对局速览 研究档案 research/hunt-sim/： - players/：10 人配置（LLM 亲笔）+策略自述+逐局去留决策+人设终评+退游者重访 - rounds/：v1 三轮（R0 教学+R1/R2 真人快速）+ v2 复测两轮，共 48 局全记录 - analysis/01-04：数值曲线/音频信息设计/协作社交/上手留存四视角报告 - synthesis.md（S1-S9 裁定）、metrics.md/metrics-v2.md（两版对比总账）、report.md（总报告） v1 核心发现：10 人 3 轮 28 局 100% 胜率 26S/营地零损耗；击杀垄断（专家单人 30/39）； 呼喊 3 次/28 局应答 0；N/S 前后判读仅 63/69% 可命中；四种退游死因 （失衡/社交真空/交互摩擦/观光无聊）→ 详见 report.md
368 lines
5.6 KiB
JSON
368 lines
5.6 KiB
JSON
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