In the context of our Q-Learning algorithm, select all which are true:

we calculate a quality score for each (environment, action) pair

we use a high value for gamma, the discount, to place more emphasis on future feedback; a lower value places more emphasis on immediate feeback

absent some limit or threshold, our Q-Learning algorithm will run forever

Our quality score is the delta (difference) between immediate and future feedback