Including Collective Intelligence in Human-Machine Interactive Decision-Making under Time Constraints

In this paper, we discuss the problem of time constraints in the stopping criteria for managing human-machine interaction that involves a misapprehension of decision makers. We propose a methodology that locates best alternatives by including collective intelligence on behavioral patterns of groups in a time-critical decision process for mitigating the misapprehension. The results of simulation and its statistical tests describe that the proposed methodology allows 99.9% or better decision makers to locate best alternatives in an earlier time period and contributes to the stopping criteria by introducing alert and confirm built-in functions into human-machine system design.