2021/11/05 by Gheorghe Tecuci, Dorin Marcu, Tecuci, Gheorghe +5
Computer Science · #AI-based Problem Solving and Planning #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Logic, Reasoning, and Knowledge #Semantic Web and Ontologies #cs.AI
paper · pdf · doi:10.48550/arxiv.2111.03728
Presented at AAAI FSS-21: Artificial Intelligence in Government and Public Sector, Washington, DC, USA
arxiv created 2021/11/05 · openalex publication_date 2021/11/05 · arxiv updated 2021/11/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We present a model of sense-making that greatly facilitates the collaboration between an intelligent analyst and a knowledge-based agent. It is a general model grounded in the science of evidence and the scientific method of hypothesis generation and testing, where sense-making hypotheses that explain an observation are generated, relevant evidence is then discovered, and the hypotheses are tested based on the discovered evidence. We illustrate how the model enables an analyst to directly instruct the agent to understand situations involving the possible production of weapons (e.g., chemical warfare agents) and how the agent becomes increasingly more competent in understanding other situations from that domain (e.g., possible production of centrifuge-enriched uranium or of stealth fighter aircraft).