Learning by instruction is one of the most common forms of learning, and a number of research efforts have modeled the cognitive process of instruction following, with many successes. However, most computational models remain brittle with respect to the given instructions, and they lack the ability to adapt dynamically to variants of the instructions. This paper aims to illustrate modeling constructs designed to make instruction following more robust, including (1) more flexible grounding of language to execution, (2) processing of instructions that allows for inference of implicit instruction knowledge, and (3) dynamic, interactive clarification of instructions during both the learning and execution stages. Examples in the context of a paired-associates task and a visual-search task are discussed.

中文翻译：

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教学中的互动基础和推理

教学中学习是最常见的学习形式之一，许多研究工作已经对遵循教学的认知过程进行了建模，并取得了许多成功。然而，大多数计算模型对于给定指令仍然很脆弱，并且它们缺乏动态适应指令变体的能力。本文旨在说明旨在使指令遵循更稳健的建模结构，包括 (1) 更灵活的语言执行基础，(2) 允许推断隐式指令知识的指令处理，以及 (3) 动态、交互式澄清在学习和执行阶段的指令。讨论了配对关联任务和视觉搜索任务上下文中的示例。