Title :
How Learning Enables Intelligence Analysts to Rapidly Develop Practical Cognitive Assistants
Author :
Tecuci, Gheorghe ; Boicu, Mihai ; Marcu, Dorin ; Schum, David
Author_Institution :
Learning Agents Center, George Mason Univ., Fairfax, VA, USA
Abstract :
This paper overviews an end-to-end learning-based approach to the rapid development of practical cognitive assistants for intelligence analysis. A learning agent shell has been trained by a knowledge engineer with general evidence-based reasoning knowledge for intelligence analysis. This agent is further trained by an expert analyst how to analyze complex hypotheses from a given intelligence analysis domain. The resulting cognitive assistant is used by a typical analyst to rapidly analyze hypotheses from agent´s area of expertise. During its use, the agent continues to learn reasoning patterns from its user. This approach has been implemented and practical agents have been developed and used. This is a significant application of machine learning to agents development in intelligence analysis that can be generalized to many other domains involving evidence-based reasoning, including medicine, law, and science.
Keywords :
case-based reasoning; knowledge based systems; learning (artificial intelligence); multi-agent systems; ontologies (artificial intelligence); complex hypotheses analysis; end-to-end learning-based approach; general evidence-based reasoning knowledge; intelligence analysis domain; intelligence analysts; learning agent shell; ontology; practical cognitive assistant development; reasoning pattern learning; rule learning; Cognition; Force; Government; Knowledge based systems; Ontologies; Problem-solving; cognitive assistant; evidence-based reasoning; intelligence analysis; learning agent shell; ontology; rule learning;
Conference_Titel :
Machine Learning and Applications (ICMLA), 2013 12th International Conference on
Conference_Location :
Miami, FL
DOI :
10.1109/ICMLA.2013.25
