Computational Cognitive Science
The Computational Cognitive Science group aims at advancing the theoretical foundations of computational explanations in cognitive science.
Our approach is characterized by the use of conceptual analysis, computational and formal modeling, computational complexity analysis, and simulations. The formalisms studied by the group span the gamut of cognitive science modeling approaches, including symbolic, neural network, probabilistic (e.g. Bayesian), dynamical, logic, robotic, agent-based, and heuristic models of cognition.
The group's research focuses specifically on the computability and scalability of explanations of core cognitive abilities, such as inference, prediction, analogizing, and communicating.