ABSTRACT
This chapter presents a novel view of certification and evaluation in the specific case of “human–like” systems (HLS). Such systems are knowledge intensive. Thus, knowledge acquisition is a key issue to understanding, implementing, and evaluating related knowledge bases. Evaluation is incremental and situational. Experiences on the MESSAGE and HORSES projects have lead to the Situation Recognition Analytical Reasoning model that is proposed for use in knowledge acquisition and evaluation. This approach leads to the concept of Integrated Human–Machine Intelligence where HLS certification is viewed as an incremental process of operational knowledge acquisition.
