Computational models for intention handling

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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.