Explaining intuitive difficulty judgments by modeling physical effort and risk


How do we estimate the difficulty of performing a new task, a task we’ve never tried before such as making a sculpture, a birthday cake, or building a tower with LEGO blocks? Estimating difficulty helps us appreciate others’ accomplishments, and plays a critical role in deciding whether to undertake new tasks ourselves. Here we give a computational account of how humans judge the difficulty of a range of physical construction tasks, whererby the goal is to go from an inital configuration (e.g. blocks scattered on the floor) to a target configuration (e.g. a block tower). Our model takes into account two key aspects that influence construction difficulty: physical effort and physical risk. Physical effort captures the minimal raw work needed to transport all objects to their final positions and is computed using a hybrid task-and-motion planner. Physical risk corresponds to the precision with which objects must be transported for success, and is computed using noisy physics simulations; it reflects the costs (e.g., attention, coordination and fine motor movements) needed to ensure precise motion. We show that the full effort-risk model captures human estimates of difficulty and construction time better than either component alone, and that difficulty judgments are selectively sensitive to effort and risk in a task-dependent manner.

Yildirim I., Saeed B., Bennett-Pierre G., Gerstenberg T., Tenenbaum J. B., Gweon H. (2019). Explaining intuitive difficulty judgments by modeling physical effort and risk. In Proceedings of the 41st Annual Conference of the Cognitive Science Society.

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