# What is the KWIK Framework?

"...for learning transition dynamics...in the KWIK framework."

The above is part of a paper's conclusion - and I don't really seem to understand what the KWIK framework is. In the details of the paper, is a brief highlight of the KWIK conditions for a learning algorithm, which go as follows (I paraphrase):

1. All predictions must be accurate (assuming a valid hypotheses class)
2. However the learning algorithm may also return $$\perp$$, which indicates that it cannot yet predict the output for this input.

A quick Google Search brought me to this paper from ICML 2008, but it is a little difficult to comprehend without a detailed read.

Could someone please help me understand what the KWIK framework is, and what implication does it have for a learning algorithm to satisfy KWIK conditions? An explanation that starts at simple and goes to fairly advanced discussions is appreciated.

Thanks a lot!

• What about this presentation about the very same paper from ICML 2008? It has less pages and is more simply put than the paper. – mico May 3 at 9:03