Tong, Jonathan C.H.Jonathan C.H.TongHsu, Yung-FongYung-FongHsuLiau, Churn-JungChurn-JungLiau2025-10-302025-10-302024-05-20https://www.scopus.com/pages/publications/105016641818?origin=resultslisthttps://scholars.lib.ntu.edu.tw/handle/123456789/733310This short paper is the status report of a project in progress. We aim to model human-like agents' decision-making behaviors under risks with neural-symbolic approach. Our model integrates the learning, reasoning, and emotional aspects of an agent and takes the dual process thinking into consideration when the agent is making a decision. The model construction is based on real behavioral and brain imaging data collected in a lottery gambling experiment. We present the model architecture including its main modules and the interactions between them.Decision makingBrain-imaging dataDecision-making behaviorsDual processEmotional aspectExtended abstractsHuman-like agentsMain moduleModel constructionModeling architectureSymbolic computingArtificial intelligence[SDGs]SDG16journal article10.1609/aaaiss.v3i1.31288