2015/06/16 by Ernest Davis, Gary Marcus, Davis, Ernest +1
Computer Science · Psychology · Social Sciences · #Artificial Intelligence (cs.AI) #Cognitive Science and Mapping #FOS: Computer and information sciences #Science Education and Pedagogy #Visual and Cognitive Learning Processes
paper · pdf · doi:10.48550/arxiv.1506.04956
openalex publication_date 2015/06/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
It has been proposed that human physical reasoning consists largely of running "physics engines in the head" in which the future trajectory of the physical system under consideration is computed precisely using accurate scientific theories. In such models, uncertainty and incomplete knowledge is dealt with by sampling probabilistically over the space of possible trajectories ("Monte Carlo simulation"). We argue that such simulation-based models are too weak, in that there are many important aspects of human physical reasoning that cannot be carried out this way, or can only be carried out very inefficiently; and too strong, in that humans make large systematic errors that the models cannot account for. We conclude that simulation-based reasoning makes up at most a small part of a larger system that encompasses a wide range of additional cognitive processes.