Title: Theory / Important / CS / Algo / Artificial intelligence / Value Learning

Name: specification problem
Definition: problem of defining the behavior that we would want to see from our AI system
Page: https://www.alignmentforum.org/s/4dHMdK5TLN6xcqtyc/p/5eX8ko7GCxwR5N9mN
Chapter: 1 What is ambitious value learning?
Context: AI

Name: AI Safety problem
Definition: How to compute the behavior that we want to see in an AI
Page: https://www.alignmentforum.org/s/4dHMdK5TLN6xcqtyc/p/5eX8ko7GCxwR5N9mN
Chapter: 1 What is ambitious value learning?

Name: Inverse reinforcement learning
Page: https://www.alignmentforum.org/s/4dHMdK5TLN6xcqtyc/p/5eX8ko7GCxwR5N9mN
Chapter: 1 What is ambitious value learning?
Abbreviation: IRL

Name: The goal inference problem
Definition: Find any reasonable representation of any reasonable approximation to what that human wants.
Page: https://www.alignmentforum.org/s/4dHMdK5TLN6xcqtyc/p/h9DesGT3WT9u2k7Hr
Chapter: 2The easy goal inference problem is still hard

Name: The easy goal inference problem
Definition: Goal inference problem, given no algorithmic limitations and access to the complete human policy — a lookup table of what a human would do after making any sequence of observations .
Page: https://www.alignmentforum.org/s/4dHMdK5TLN6xcqtyc/p/h9DesGT3WT9u2k7Hr
Chapter: 2The easy goal inference problem is still hard

Name: The very easy goal inference problem
Definition: Similar to easy goal inference problem, but restrained to a very narrow domain
Page: https://www.alignmentforum.org/s/4dHMdK5TLN6xcqtyc/p/h9DesGT3WT9u2k7Hr
Chapter: 2 The easy goal inference problem is still hard
Example: Driving
Counterexample: designing a city, running a company, or setting good policies.