Predecessor Features

Understand

Any reinforcement learning system must be able to identify which past events contributed to observed outcomes, a problem known as credit assignment.

• A common solution to this problem is to use an eligibility trace to assign credit to recency-weighted set of experienced events.
• However, in many realistic tasks, the set of recently experienced events are only one of the many possible action events that could have preceded the current outcome.
• This suggests that reinforcement learning can be made more efficient by allowing credit assignment to any viable preceding state, rather than only those most recently experienced.