Hi all, Genifer is looking for developers, we have the following tasks:
1. We need to implement a Bayesian network belief propagation algorithm based on factor graphs. The algorithm has been figured out and is 90% completed in Lisp, however the probability calculations were very complicated so it was unfinished. We need to port this to the new Clojure code. For this task, basic understanding of Bayes nets is preferred. 2. Inductive learner. Preferably with background in logic-based inductive learning, aka ILP (inductive logic programming). 3. Inductive learning 2. More advanced maths is needed for this task. Genifer is now using an "algebraic logic" having the structure of a non-commutative semi-ring. I have a vague feeling that it might be possible to transfer spatial learning techniques to the symbolic realm using algebraic geometry as a bridge. SVM (support vector machine) is a powerful spatial learner. Perhaps we can do to statistical logic learning what SVM has done to statistical spatial learning? 4. Hierarchical clustering of the KB. I am developing code for the distance metric (ie, similarity measure). Perhaps I need a partner who can implement the clustering code. PS: The code is in Clojure, but any JVM language such as Java, Scala, will do as well. -- *KY* *"The ultimate goal of mathematics is to eliminate any need for intelligent thought"* -- Alfred North Whitehead ------------------------------------------- AGI Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/21088071-c97d2393 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-2484a968 Powered by Listbox: http://www.listbox.com
