Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces — mentioned by gwern

Tue, 31 Jul 2018 17:19:14 GMT

> Qualitative items such as the ones listed are important for customer focused environments, however, I'm not sure if AI can account for such factors. One of the nice things you can do with optimization problems is plug humans into the loop as oracles. Often, 'we know it when we see it', and we can do pairwise comparisons of 2 possibilities. So you can train a ML model based on win/loss comparisons and it'll learn to take into account the softer qualitative aspects via preference learning. A recent example you might remember from the press: "Deep reinforcement learning from human preferences"…

Paper and discussion history. A mention is not an endorsement.

Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces · HackerPapers discussions

Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces — mentioned by gwern