To be robust to surprising developments, an intelligent agent must be able to respond to many different types of unexpected change in the world. To date, there are no general frameworks for defining and characterizing the types of environment changes that are possible. We introduce a formal and theoretical framework for defining and categorizing environment transformations, changes to the world an agent inhabits. We introduce two types of environment transformation: R-transformations which modify environment dynamics and T-transformations which modify the generation process that produces scenarios. We present a new language for describing domains, scenario generators, and transformations, called the Transformation and Simulator Abstraction Language (T-SAL), and a logical formalism that rigorously defines these concepts. Then, we offer the first formal and computational set of tests for eight categories of environment transformations. This domain-independent framework paves the way for describing unambiguous classes of novelty, constrained and domain-independent random generation of environment transformations, replication of environment transformation studies, and fair evaluation of agent robustness.

翻译：为应对突发性发展，智能体必须能够响应世界中多种不同类型的意外变化。目前，尚无通用框架可用于定义和表征可能的环境变化类型。我们提出一个形式化理论框架，用于定义和分类环境变换（即智能体所处世界的变化）。我们引入两类环境变换：修改环境动态的R变换，以及修改生成场景过程的T变换。我们提出一种用于描述领域、场景生成器和变换的新语言——变换与模拟器抽象语言（T-SAL），并建立一种严格定义这些概念的逻辑形式体系。随后，我们提供首套针对八类环境变换的形式化计算测试集。这一领域无关框架为以下方面铺平道路：描述无歧义的新颖性类别、约束化且领域无关的环境变换随机生成、环境变换研究的可复现性，以及智能体鲁棒性的公平评估。