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.

为了应对世界千变万化，智能代理的关键在于对环境的多样性进行响应。本研究提出了环境转化（可分为R-transformations和T-transformations两类）的概念和形式化理论框架，引入了新的描述环境和变形的语言T-SAL，提供了一套涵盖8类情境变化的测试，以期为新颖和偶发情境提供明确的分类，为代理的鲁棒性提供公正的评估。

一种用于描述一般环境中新颖环境变换的框架