Now Python code with the knowledge graph for the track described in the ELEKTRONIKPRAXIS article, including a meaning transformer, is waiting for you!

Its nodes describe the driving states and its edges describe physical processes. Understand how an AI at its core works with the help of this simple neural network! And how you can mathematically express and understand the essence of the world’s things with their often dynamic relationships.

Solve your tricky multi-objective problems, tame the flood of data and master complexity! This will enable you to make incomparably better use of space, time, matter and energy than you do today, and increase your competitiveness.

Instell the virtual Python-Environment and play with the neural network with the race track modeled as a graph.

Click on the SpeedProfileOptimisation.ipynb file in the left-hand window of the Python environment and start the program with the two arrows in the menu list.