{"pk":29222,"title":"Predicting human decisions in a sequential planning puzzle with a large state space","subtitle":null,"abstract":"We study human sequential decision-making in large state spaces using a puzzle game called Rush Hour. A puzzle consistsof a dense configuration of rectangular cars on a 6x6 grid. Each car moves only horizontally or vertically. The goal isto move a target car to an exit. In a given state (board position), a subject (n=86) could move a car, restart the puzzle,or surrender. A move is correct if it reduces the distance (number of moves) to the goal. Using mixed-effects logisticregression modeling, we find that the probabilities of an error, a restart, and a surrender are higher with a longer distanceto goal, higher mobility, and when the previous move was an error. The effects of distance to goal and mobility areconsistent with tree search. As a next step, we plan to investigate the heuristics that people might use for such tree search.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Member Abstracts","is_remote":true,"remote_url":"https://escholarship.org/uc/item/2nx113qk","frozenauthors":[{"first_name":"Yichen","middle_name":"","last_name":"Li","name_suffix":"","institution":"New York University","department":""},{"first_name":"Zahy","middle_name":"","last_name":"Bnaya","name_suffix":"","institution":"New York University","department":""},{"first_name":"Wei","middle_name":"Ji","last_name":"Ma","name_suffix":"","institution":"New York University","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2019-01-01T13:00:00-05:00","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/29222/galley/19093/download/"}]}