Human Motor Planning Approaches but Fails to Achieve Optimal Indecisiveness

• Christopher Peters, Biomedical Engineering, University of Delaware

• Joshua Cashaback, Biomedical Engineering, University of Delaware

From a driver swerving to avoid an accident to a batter tracking a pitch, making rapid decisions is a ubiquitous and vital human ability, however we are not always fast enough. Indecisions, or  failures to execute a decision before a time constraint, are frequently observed in human behavior yet their role in human decision making is largely unexplored. We tested the hypothesis that optimal behavior that maximizes expected reward in a motor decision making task will result in making indecisions, predicting that humans would make the optimal amount. The task was modeled computationally as an optimal stopping time problem where human participants selected a time to stop waiting for sensory evidence to react to and proceed to guess randomly to maximize points earned. Participants approached optimality by adjusting their stopping times to account for internal delays and avoid suboptimal amounts of indecisions. Despite this, participants were still suboptimal in their decision times and indecision rates compared to the optimal model, possibly showing a bias towards making decisions with sensory evidence over random guessing and a lack of consideration for additional delays and uncertainties involved in guessing. Model predictions suggested the optimal strategy would result in making indecisions in all conditions but one where instant random guessing was the ideal strategy due to reaction and movement delays. Applications of understanding how humans make choices include athletic, emergency service, and military settings where optimization of rapid decision making is relevant to improving performance.