I will analyze some selected examples of complex behaviors through the lens of decision-making theory. The aim is to identify minimal models that explain how agents process information and perform actions.

Prof. Antonio Celani received his PhD at Politecnico di Torino, Italy in 1998. After post-doctoral fellowships at Max Planck Institute in Munich and at the Observatoire de la Côte d'Azur he became researcher for the French National Research Council (CNRS) in 2000. In 2007 he moved to the Institut Pasteur Paris as a research director where he started working at the interface between physics and biology. He joined ICTP in 2014 to contribute to the establishment of the Quantitative Life Sciences Section. He currently works on the theory of Reinforcement Learning and its applications to physics and biology.