ML-TIPN: An Algorithm for Automated Acquisition of Domain Models based on Time Interval Petri Nets

摘要: Extended Petri Nets have been applied to artificial intelligence reasoning processes, in areas such as planning, uncertainty reasoning, knowledgebased intelligent systems, and qualitative simulation. Creating Net domain models faces the same challenges that confront all knowledge-intensive AI performance systems: model specification, knowledge acquisition, refinement. Thus, a fundamental question investigate is degree which automation can be used. This paper formulates learning task presents first machine method for Time Interval (TIPN) models. In preliminary evaluation within damage control domain, learned nearly perfect of fire spread augmented with temporal spatial data.