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R-CAST is a group decision support system based on research on naturalistic decision making. Its architecture, based on multiple software agents, supports decision-making teams by anticipating information relevant to their decisions based on a shared mental model about the context of decision making. ==Principles of design== In this digital information age, decision-making teams are often flooded with an overwhelming amount of information. This leads to two challenges: * First, a human decision maker can be overloaded with information and have difficulty making good decisions in a timely manner. * Second, members of a team may have difficulty determining what information a teammate actually needs, and hence what information needs to be shared with him/her. The R-CAST technology aims to address both of these challenges. The R-CAST approach is based on four major concepts: # Agents use a model of human decision making process (called recognition primed decision () model) to link decision-making tasks to information relevant to the decisions. # The computational RPD model in R-CAST uses a knowledge structure (called experience knowledge) that captures knowledge relevant to decision-making. # Three types of relevant information can be anticipated from experience knowledge and inference rules, relating to: ## matching current situation to known experience (i.e., cues), ## evaluating multiple decision options, and ## detecting anomalies after a decision is made so that the original decision can be modified accordingly. # The computational RPD model serves as a shared DM process between agents and human in a team, which enables agents to share relevant information to other teammates, whether they are software agents or human. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「R-CAST」の詳細全文を読む スポンサード リンク
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