The International Workshop on Principles of Diagnosis is an annual event that started in 1989, rooted in the Artificial Intelligence (AI) community. Its focus is on theories, principles and computational techniques for diagnosis, monitoring, testing, reconfiguration and repair of complex systems implemented in hardware, software, and a combination of these. Transfer of these theories, principles and techniques to industry related disciplines is among the important topics of the workshop.

DX-2004 particularly encourages the interaction and the exchange of theories, techniques, and experiences among scientists with diverse interests to diagnosis and different backgrounds: Artificial Intelligence, Control Theory, Systems Engineering, Software Engineering and other related areas.

DX is a lively forum that has traditionally adopted a single-track program and limited the number of participants in order to support detailed technical exchange and debate. We welcome papers in a variety of areas related but not limited to:

• Formal theories and computational methods for: diagnosis, monitoring, testing, repair, reconfiguration, fault tolerance, diagnosability analysis and related topics.
• Modeling for diagnosis: symbolic, numeric, discrete, continuous, hybrid, probabilistic, functional, behavioral, qualitative, abstractions and approximations.
• Computational issues: controlling combinatorial explosion, use of structural and hierarchical knowledge, focusing strategies, resource-bounded reasoning.
• The diagnosis process: strategies for measurement selection, sensor placement, experiment design, active testing, embedded diagnosis systems, preventive diagnosis, fault tolerance strategies, distributed diagnosis.
• Bridge between DX and other areas: FDI control based techniques, statistical and probabilistic methods, design, model checking, machine learning, non-monotonic reasoning, planning, execution, real time languages, software verification and validation, debugging, hardware testing.
• Applications and technology transfer: real-world applications and integrated systems in a wide range of fields including transport systems, space and aeronautics, process industry, biomedical. Success (or failure) stories are especially welcome.