Symbolic methods and optimization

What do we mean when we address research projects, projects and concrete solutions using symbolic AI?

Symbolic methods process symbols, e.g. in the form of logics, which are understandable and interpretable by humans. In contrast, subsymbolic AI is distinct from this: Here, we are dealing with many, unordered data points that cannot be easily interpreted. 

Example: Everyone can imagine something under the system state "good" (symbolic). From a time series of binary data it is very difficult for humans to find out the system state (sub-symbolic).

• Expert systems (Knowledge Modeling)

• Diagnosis (Application field industry and SME, possible with small amount of production data)
• Reconfiguration (Industry application field, redundancies necessary)
• Explainable AI (Example project: KOSMOX)

• Optimization of production planning and control (Example project: SUPPORT)
• Logistics optimization (Example project: IMAGINE)
• Parameters optimization (Example project: KI4LSA)

• Consulting
• Scientific monitoring
• Implementation