Computational models for intention handling

这项研究致力于扩大计算认知理论的范围，以理解人类的执行控制功能，也就是可能被视为“人类操作系统”的功能。一个基本的问题是，人类大脑如何设定面向未来的意图：决定在未来的某个时间执行一些行动(比如在一天结束时记得买牛奶)，以及如果和当环境提示表明条件适合这样做时，随后执行该活动。意图在智力计算理论中的作用是引导注意力和推理资源。这项研究在计算机模拟和实验室实验的基础上，发展了关于人类认知架构如何表达和操纵意图的认知理论。这对于理解人类如何同时完成几项任务具有实际意义。理解支持未来意图的认知微结构与各种认知工程努力有关，例如，对于支持人类在动态环境中表现的系统的设计，在动态环境中，任务被中断，然后必须在适当的时间后或环境变化时恢复。被中断的任务可以被视为未来恢复一项活动的定向意图，了解哪些因素影响这种意图是否可能被记住并成功执行是很重要的。

The research is concerned with expanding the scope of computational cognitive theories to understand the human executive control function, or what might be viewed as the 'human operating system.' One basic question is how the human brain sets a future-directed intention: a decision to execute some action at a future time (such as remembering to buy milk at the end of the day) and the subsequent execution that activity, if and when environmental cues signal that conditions are appropriate to do so. The role of intentions in computational theories of intelligence is to direct attention and reasoning resources. This research develops cognitive theories, based on computer simulations and laboratory experiments, about how intentions are represented and manipulated by the human cognitive architecture. This has practical implications for understanding how humans can do several tasks concurrently. Understanding the cognitive microstructure that supports future-directed intentions is relevant to various cognitive engineering efforts, e.g., for the design of systems that support human performance in dynamic environments in which tasks are interrupted and then must be resumed after some appropriate time or when the environment changes. Interrupted tasks can be viewed as a future directed intention to resume an activity,and it is important to understand what kinds of factors impact whether or not such an intention is likely to be remembered and executed successfully.