"A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results from an investigation into using discrete and fuzzy dynamical system representations within the XCSF Learning Classifier System. In particular, asynchronous Random Boolean Networks are used to represent the traditional condition-action production system rules in the discrete case and asynchronous Fuzzy Logic Networks in the continuous-valued case. It is shown possible to use self-adaptive, open-ended evolution to design an ensemble of such dynamical systems within XCSF to solve a number of well-known test problems."

"The paper is written in the form of introduction to the subject, with much of the material accessible to advanced high school students. However, in the part of the survey concerning configurations of lines in general position in the three-dimensional space the exposition is free from any background restrictions. We have added few new results, fixed few misprints and terminological inaccuracies and expanded the reference list. Notice that some of the results presented in the paper appeared in other papers without appropriate references."

"If anyone is interested in chatting about what makes a fund a more "successful business" drop me a line. Getting more AUM (assets under management) is the goal of most funds. The maintenance fees of 2% are ridiculously high.

The magic threshold in the business is $100m AUM with +36 months of exposure because these are the operational levels, where most institutions start looking around at allocations. Please note instituional sales cycles for allocations are 9-12 months, while family offices are estimated at 12-18 months."

"Made possible by an $8 million gift from the entrepreneurs for whom the program is named, the Rajendra and Neera Singh Program in Market and Social Systems Engineering, MKSE, will be the first course of study to fully integrate the disciplines needed in this emerging science. The intellectual core of the program will encompass network science, algorithmic game theory and other disciplines relevant to engineers and scientists as they consider human incentives and behavior in developing modern technological systems."