"My main interest is the overlap between software engineering
and computational science."

By allowing the brains of these digital organisms to evolve freely in their model the researchers were able to show that  the transition to cooperative society  leads to the strongest selection for bigger brains. Bigger brains essentially did better as cooperation increased.

# here is the new-style Borg (not much more complex then the "old-style")
class Borg(object):
_state = {}
def __new__(cls, *p, **k):
self = object.__new__(cls, *p, **k)
self.__dict__ = cls._state
return self

class Borg:
__shared_state = {}
def __init__(self):
self.__dict__ = self.__shared_state
# and whatever else you want in your class -- that's all!

StackExchange for Scientific Computing and Computation

Dr. Steve Strogatz wonders if we've reached the limits of human scientific understanding, and should soon turn the reins of research over to robots. Cold, calculating robots. Then, Dr. Hod Lipson and Michael Schmidt walk us through the workings of a revolutionary computer program that they developed--a program that can deduce mathematical relationships in nature, through simple observation.

In a matter of minutes the algorithm converged on Newton's second law of motion: f = ma. What took humanity tens of thousands of years to accomplish was completed on 32-cores in essentially no time at all.

Lots of useful links

We introduce a machine learning model to predict atomization energies of a diverse set of organic molecules, based on nuclear charges and atomic positions only. The problem of solving the molecular Schr"odinger equation is mapped onto a non-linear statistical regression problem of reduced complexity. Regression models are trained on and compared to atomization energies computed with hybrid density-functional theory. Cross-validation over more than seven thousand small organic molecules yields a mean absolute error of ~10 kcal/mol. Applicability is demonstrated for the prediction of molecular atomization potential energy curves.

three methods to approach philo- sophical problems informationally: Minimalism, the Method of Abstrac- tion and Constructionism.

REBOUND is a new multi-purpose N-body code which is freely available under an open-source license. It was designed for collisional dynamics such as planetary rings but can also solve the classical N-body problem. It is highly modular and can be customized easily to work on a wide variety of different problems in astrophysics and beyond.

This book is an introduction, entirely by example, to the possibilities of using computer models as tools in philosophical research in general and in philosophical logic in particular. The accompanying software contains a variety of working examples, in color and often operating dynamically, embedded in a text which parallels that of the book. In order to facilitate further experimentation and further research, we have also included all basic source code in the software.