Current research interests

  • Learning and decision-making in biological and artificial systems.
  • Optimality of inference methods.
  • Uncertainty in decision-making systems and algorithms.
  • Emergence of modularity, abstraction, and complex structures.
  • Systems with limited information processing capabilities.

Publications

  • Gottwald S., Braun D.A., The Two Kinds of Free Energy and the Bayesian Revolution, under review (arXiv)
  • Lindig-León C., Gottwald S., Braun D.A., Analyzing Abstraction and Hierarchical Decision-Making in Absolute Identification by Information-Theoretic Bounded Rationality, 2019, Frontiers in Neuroscience 13, www.frontiersin.org
  • Hihn H., Gottwald S., Braun D.A., An Information-theoretic On-line Learning Principle for Specialization in Hierarchical Decision-Making Systems, 2019, IEEE 58th Conference on Decision and Control, IEEE
  • Gottwald S., Braun D.A., Bounded Rational Decision-Making from Elementary Computations That Reduce Uncertainty, 2019, Entropy, MDPI (arXiv)
  • Gottwald S., Braun D.A., Systems of bounded rational agents with information-theoretic constraints, 2019, Neural Computation, MIT Press (arXiv)
  • Schach S., Gottwald S., Braun D.A., Quantifying Motor Task Performance by Bounded Rational Decision Theory, 2018, Frontiers in Neuroscience
  • Hihn H., Gottwald S., Braun D.A., Bounded Rational Decision-Making with Adaptive Neural Network Priors, 2018, Artificial Neural Networks in Pattern Recognition, Springer (arXiv)
  • Gottwald S., Two-term spectral asymptotics for the Dirichlet pseudo-relativistic kinetic energy operator on a bounded domain, 2018, Annales Henri Poincaré, Springer (arXiv)


For more information visit https://gttwld.de.