首页|Carnegie Mellon University Reports Findings in Artificial Intelligence (Applying Generative Artificial Intelligence to cognitive models of decision making)
Carnegie Mellon University Reports Findings in Artificial Intelligence (Applying Generative Artificial Intelligence to cognitive models of decision making)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligenc e is the subject of a report. According to news reporting from Pittsburgh, Penns ylvania, by NewsRx journalists, research stated, “Generative Artificial Intellig ence has made significant impacts in many fields, including computational cognit ive modeling of decision making, although these applications have not yet been t heoretically related to each other. This work introduces a categorization of app lications of Generative Artificial Intelligence to cognitive models of decision making.” Financial support for this research came from Army Research Office. The news correspondents obtained a quote from the research from Carnegie Mellon University, “This categorization is used to compare the existing literature and to provide insight into the design of an ablation study to evaluate our proposed model in three experimental paradigms. These experiments used for model compari son involve modeling human learning and decision making based on both visual inf ormation and natural language, in tasks that vary in realism and complexity. Thi s comparison of applications takes as its basis Instance-Based Learning Theory, a theory of experiential decision making from which many models have emerged and been applied to a variety of domains and applications. The best performing mode l from the ablation we performed used a generative model to both create memory r epresentations as well as predict participant actions. The results of this compa rison demonstrates the importance of generative models in both forming memories and predicting actions in decision-modeling research. In this work, we present a model that integrates generative and cognitive models, using a variety of stimu li, applications, and training methods.”
PittsburghPennsylvaniaUnited StatesNorth and Central AmericaArtificial IntelligenceEmerging TechnologiesMach ine Learning
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