HEXIS: Compiling Skills into Extended Finite State Machines· HEXIS: 编译技能为扩展有限状态机
Agent skills provide reusable knowledge and instructions, yet agents must repeatedly infer how to apply them and which operation should follow. This couples task reasoning with control decisions, allowing prescribed steps to be omitted or applied incorrectly. We introduce HEXIS, which compiles agent skills into extended finite state machines that separate knowledge from control flow. Skill knowledge is incorporated into local instructions that guide reasoning and generation within states. The machine records execution progress and intermediate results, while explicit transition conditions determine subsequent operations. Our incremental compiler first maps skill clauses and tool interfaces to state operations, local instructions, data bindings, and transitions. It then aligns development t
将技能编译为扩展有限状态机，实现知识与控制分离。
- 核心方法
- 通过HEXIS框架，将技能知识编译成扩展有限状态机，每状态包含本地指令指导推理和生成，明确的转换条件决定后续操作。
- 适合谁读
- 研究者、工程师
- 要解决的问题
- 现有的智能体技能应用时，任务推理与控制决策紧密耦合，容易导致步骤遗漏或错误执行。
- 关键实验
- 未提供
- 主要贡献
- 提出HEXIS编译器，实现技能知识与控制流程的分离，提高技能执行的准确性和可重用性。
- 意义与局限
- 该方法可以更有效地管理和执行复杂任务，但目前缺乏实验验证其实际效果。