While cetaceans clearly show social learning in a wide variety of contexts, to label this as hides more than it reveals: we need a taxonomy of culture to tease apart the differences rather than hiding them in a catch-all category.

We give an account of some relationships between the principles of Constant and Atom Exchangeability and various generalizations of the Principle of Instantial Relevance within the framework of Inductive Logic. In particular we demonstrate some surprising and somewhat counterintuitive dependencies of these relationships on ostensibly unimportant parameters, such as the number of predicates in the overlying language.

Where behavior defies economic analysis, one explanation is that individuals consider more than the immediate payoff. We present evidence that noneconomic factors influence behavior. Attractiveness influences offers in the Ultimatum and Dictator Games. Facial resemblance, a cue of relatedness, increases trusting in a two-node trust game. Only by considering the range of possible influences will game-playing behavior be explained.

It is an interesting fact of our time that some of the best studies of communism and Marxism have been written by Catholic scholars. This book, based on a series of television programs in St. Louis aims at presenting an historical and theoretical understanding of the emergence of Marxism and the development of Communism. Written for the intelligent lay reader as an introduction to a complex subject, the treatment is lucid and balanced.—R. J. B.

We apply an online optimization process based on machine learning to the production of Bose-Einstein condensates. BEC is typically created with an exponential evaporation ramp that is optimal for ergodic dynamics with two-body s-wave interactions and no other loss rates, but likely sub-optimal for real experiments. Through repeated machine-controlled scientific experimentation and observations our ’learner’ discovers an optimal evaporation ramp for BEC production. In contrast to previous work, our learner uses a Gaussian process to develop a statistical model of the (...) relationship between the parameters it controls and the quality of the BEC produced. We demonstrate that the Gaussian process machine learner is able to discover a ramp that produces high quality BECs in 10 times fewer iterations than a previously used online optimization technique. Furthermore, we show the internal model developed can be used to determine which parameters are essential in BEC creation and which are unimportant, providing insight into the optimization process of the system. (shrink)