AI 中文总结
CORTEX通过外部经验验证层连接专用智能体，以元控制器决策精确重放、适配或综合，实现可增长且无需改变模型权重的通用智能路径。
AI 中文摘要
一个智能体今天能解决某个任务，明天却可能在新的事实、工具或支配性知识下面对同一任务。大多数智能体系统能够检索相关文本或回忆先前的对话，但它们缺乏一种有原则的方式来决定先前的解决方案何时仍然有效、何时必须调整、以及何时应被丢弃。我们提出CORTEX（上下文编排与任务经验复用），一个通用AI系统框架，通过外部经验验证层连接专用智能体。每个回合记录其任务条件、来源与工具状态、决定性谓词、证明轨迹、验证器及结果。一个元控制器选择精确重放、受检适配、全新综合或升级处理。被接受的回合可通过挑战驱动的开发循环成为任务模式与程序性策略。这赋予系统一个隐含的能力层，可在不改变模型权重的情况下增长。我们形式化了精确重放与来源版本分离的系统契约，并推导出复用何时节省计算。一个受控的双领域实现测试了精确重放核心在1,000个合成案例上的表现。完整家族保留测试测试了程序性迁移在8个临床与政策分割中的1,000个新家族案例上的表现，具有完整的全新证据基础和对无关字段及插入顺序扰动的完美不变性。迁移轨迹揭示了验证策略执行所需的工作。这些结果为通过可复用程序、类型化经验和发展性迁移实现通用智能建立了初步路径。
英文摘要
An agent can solve a task today and face the same task under new facts, tools, or governing knowledge tomorrow. Most agent systems can retrieve relevant text or recall prior conversations, but they lack a principled way to decide when a previous solution is still valid, when it must be adapted, and when it should be discarded. We introduce CORTEX (Contextual Orchestration and Reuse of Task EXperience), a general AI systems framework that connects specialized agents through an external layer of verified experience. Each episode records its task conditions, source and tool state, decisive predicates, proof trace, verifier, and outcome. A meta-controller chooses exact replay, checked adaptation, fresh synthesis, or escalation. Accepted episodes can become task patterns and procedural strategies through a challenge-driven development loop. This gives the system an implicit competence layer that can grow without changing model weights. We formalize system contracts for exact replay and source-version separation, and derive when reuse saves computation. A controlled two-domain implementation tests the exact-replay core on 1,000 synthetic cases. Complete-family holdouts test procedural transfer on 1,000 new-family cases across eight clinical and policy splits, with complete fresh-evidence grounding and perfect invariance to irrelevant-field and insertion-order perturbations. The transfer trace exposes the work required for verified strategy execution. These results establish an initial path toward general intelligence through reusable procedures, typed experience, and developmental transfer.
