__________________________________________________________________ Complex social problems modeled by multi-agent systems have very large parameter and model space. The problem of how to model, validate, detect, and plan for the event of bioterrorism is one of the these, as it requires faithful modeling of dynamic signal (bioattack event) from complex dynamic noise (normal disease outbreaks and people activities). Indeed, the dynamic and very large space – numeric or symbolic or both – nature of the problem makes manual exploration spotty, cumbersome, implicitly-biased, and thus incomplete. Scaling up multi-agent systems exacerbates these and makes the automation of exploration, modeling, and validation more critical. WIZER – a social inference engine and simulation combination capable of principled exploration through meta-models and parameters based on empirical data and knowledge – addresses the above problems by knowledge-guided & simulation-guided search. This paper describes the design of WIZER and presents a preliminary result.

A critical issue in software engineering is how to construct high assurance software systems, i.e., software systems where compelling evidence is required that the system delivers its services in a manner satisfying critical properties, such as safety and security. This two-day ICSE workshop, the third in a series of workshops on high assurance systems, will provide a forum for researchers and practitioners to exchange ideas and experiences relevant to the development of software for aerospace systems, medical systems, systems controlling nuclear power plants, and other critical systems. Participants of the SEHAS 2003 workshop will explore the opportunities for, and benefits of, synergies between three important themes—product, process, and profiling—each theme reflecting an important aspect of software development for high assurance systems. 1.

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