Computational Modeling of the Mind
Theory generation and selection is a fundamental aspect of the scientific method, critical for advancing our understanding of natural phenomena, including the human mind. This process entails generating, testing, and refining theories based on empirical evidence, aiming to identify the most accurate and comprehensive explanations. In cognitive science, researchers strive to elucidate human behavior through cognitive mechanisms that enable humans to learn, perceive, and act in the world, as well as how these processes manifest in neural activity. However, verbal theories in these fields often face challenges due to their inherent ambiguity and lack of precision, complicating the formulation of clear, testable predictions.
To address these issues, researchers increasingly turn to computational modeling. This approach enhances the precision and objectivity of theories by formalizing them into quantitative models, allowing for systematic manipulation and testing of variables. Cognitive modeling, a specialized form of computational modeling, simulates high-level human abilities (the mind), providing a more rigorous specification of theories that can be empirically compared with human data. By adjusting parameters and modifying models, researchers refine theoretical assumptions and generate novel predictions that inspire further experimentation.
In this talk, Luca will present examples of potential projects for students interested in understanding how computational modeling complements traditional experimentation. These projects will illustrate how this approach allows for more precise theory selection and advances our knowledge of the underlying mechanisms of cognition, with particular reference to human language.
As usual, pizza and refreshments will be served.