Supporting anti-terrorist analyst teams using agents with shared RPD process

Antiterrorist analysts often need to work in teams with the requirement to analyze voluminous amounts of dynamic information in order to assess potential terrorist threats. Analysts have a high cognitive demand complicated by factors that typically the information has restrict access and requires special expertise for interpretation. The goal of this research is to enhance team performance by modeling and implementing a cognitive agent architecture capable of proactively seeking, linking and sharing information using knowledge and experience distributed among team members. The agent architecture is empowered by a collaborative RPD model - a novel team-based naturalistic decision making process derived from Klein´s recognition-primed decision framework.