面向推理的编程语言：人类、符号系统与AI智能体
Toward Programming Languages for Reasoning: Humans, Symbolic Systems, and AI Agents
AI总结：
该研究提出软件开发本质是代码与语义的推理问题，针对主流语言阻碍推理的问题，推出Bosque平台与语言的简化方案，以支撑下一代编程语言发展。
摘要：
集成、组合、机械化以及AI辅助开发是软件开发未来的核心驱动主题。这些概念的根源在于计算在当今世界日益重要的地位，以及人们对更快交付更高质量功能、让更多人受益于编程自动化的诉求。这些主题及其对推动其发展的人类开发者的影响，是下一代编程语言的基础。乍看之下，机械化工具、AI智能体和人类开发者的需求，以及围绕开发速度、软件质量和软件民主化的各类目标，是一组广泛且看似多样的需求。然而，其核心是一个单一挑战——一旦解决，我们就能在所有这些领域取得根本性进展。\n我们的假设是，从根本上讲，软件开发是一个关于代码和语义的推理问题。对于实现功能的人类开发者、构建应用行为模型的符号工具，甚至是执行任务的基于语言的AI智能体而言，都是如此。尽管不同主体在推理中面临的具体问题在一定程度上存在差异，但它们有许多共同主题，而且令人惊讶的是，大多数主流语言都广泛采用了（反）特性，使得这项推理任务变得更难甚至不可行！本文针对这一挑战提出了一种新颖方法——我们没有添加新的语言特性或逻辑结构（那会给本就复杂的问题再添复杂度），而是以Bosque平台和语言的形式提出了彻底的简化方案。
英文摘要：
Integration, composition, mechanization, and AI assisted development are the driving themes in the future of software development. At their core these concepts are rooted in the increasingly important role of computing in our world, the desire to deliver functionality faster, with higher quality, and to empower more people to benefit from programmatic automation. These themes, and how they impact the human developers driving them, are the foundations for the next generation of programming languages. At first glance the needs of mechanization tools, AI agents, and human developers along with the various goals around development velocity, software quality, and software democratization are a broad and seemingly diverse set of needs. However, at their core is a single challenge that, once resolved, enables us to make radical progress in all of these areas. Our hypothesis is that, fundamentally, software development is a problem of reasoning about code and semantics. This is true for human developers implementing a feature, symbolic tools building models of application behavior, and even for language based AI agents as they perform tasks. While the particular aspects of reasoning that each agent struggles with varies to some degree, they share many common themes and, surprisingly, most mainstream languages extensively employ (anti)features that make this task harder or infeasible! This paper proposes a novel approach to this challenge -- instead of new language features or logical constructs, that add more complexity to what is already a problem of complexity, we propose radical simplification in the form of the Bosque platform and language.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
