Recent content by luciamountai

I am trying to improve my approach to Reinforcement Learning and could use some practical advice. I am particularly interested in setup choices and common mistakes. I would like to compare approaches that people have actually used rather than just theoretical suggestions. What would you tell...

I think step and deployment is the key part of this topic. A practical approach is to define the outcome you want, test it with a small example, and then check quality, speed and reliability separately. It is usually easier to troubleshoot when each change is tested on its own.

I wanted to start a broader creative experiments thread around Java. A useful angle is testing, but it also connects with automation. Different tools and workflows can produce very different results even when the goal is similar. It would be interesting to compare practical examples...