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Parallel cognition:hybrid intelligence for human-machine interaction and management 被引量:9

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摘要 As an interdisciplinary research approach,traditional cognitive science adopts mainly the experiment,induction,modeling,and validation paradigm.Such models are sometimes not applicable in cyber-physical-socialsystems (CPSSs),where the large number of human users involves severe heterogeneity and dynamics.To reduce the decision-making conflicts between people and machines in human-centered systems,we propose a new research paradigm called parallel cognition that uses the system of intelligent techniques to investigate cognitive activities and functionals in three stages:descriptive cognition based on artificial cognitive systems (ACSs),predictive cognition with computational deliberation experiments,and prescriptive cognition via parallel behavioral prescription.To make iteration of these stages constantly on-line,a hybrid learning method based on both a psychological model and user behavioral data is further proposed to adaptively learn an individual’s cognitive knowledge.Preliminary experiments on two representative scenarios,urban travel behavioral prescription and cognitive visual reasoning,indicate that our parallel cognition learning is effective and feasible for human behavioral prescription,and can thus facilitate human-machine cooperation in both complex engineering and social systems.
出处 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2022年第12期1765-1779,共15页 信息与电子工程前沿(英文版)
基金 Project supported by the National Natural Science Foundation of China (Nos.62076237,62073321,and U1811463) the Youth Innovation Promotion Association,Chinese Academy of Sciences (No.2021130)。
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