# Problem Solving in AI 1. Approximate the solution, not the problem (no special cases) 2. Drive from the problem 3. Take the agent’s point of view 4. Don’t ask the agent to achieve what it can’t measure 5. Don't ask the agent to know what it can't verify 6. Set measurable goals for subparts of the agent 7. Discriminative models are usually better than generative models 8. Work by orthogonal dimensions. Work issue by issue 9. Work on ideas, not software 10. Experience is the data of AI --- Date: 20240117 Links to: Tags: References: * [RLAI open web page](http://incompleteideas.net/rlai.cs.ualberta.ca/RLAI/richsprinciples.html)