Artificial K-lines

We propose Artificial K-lines (AKL), a structure that can be used to capture knowledge through events associated by causality. The proposed structure is inspired by the theory of memory, proposed by Minsky over 25 years ago and which has since been continuously refined. Like Artificial Neural Networks (ANN), AKL facilitates learning by capturing knowledge based on training. Unlike, and perhaps complementary to ANN, AKL is the ldquocreative polymathrdquo that continuously expands its knowledge for many different things and increases its chances for ldquocreative thinkingrdquo. We present AKL, provide a comparison with ANN, and illustrate AKLpsilas workings through an example. The example demonstrates that our structure can generate a solution where most other known technologies are either incapable of, or very complicated in, doing so.