# What does the notation $p_t = \text{max}_{i<t} p_i$ mean in algorithm 1 of the prioritized experience replay paper?

I am having a hard time converting line 6 of the prioritized experience replay algorithm from the original paper into plain English (see below):

I understand that new transitions (not visited before) are given maximal priority. On line 6 this would be done for every transition in an initial pass since the history is initialized as empty on line 2.

I’m having trouble with the notation $$p_t = \text{max}_{i. Can someone please state this in plain English? If $$t$$ = 4 for example, then $$p_t$$ = 4? How is this equal to max$$_{i.

It seems in my contrived example here, max$$_{i would be 3. I must be misreading this notation.

From my interpretation what it means is that $$p_t$$ is the priority value associated with each transition and $$p_t = max_{i means that the priority of transition number $$t$$ will be the maximum between the values of the priorities of the previous elements.
Example: since $$p_1$$ is initialized to $$1$$, all the new experiences will be too: $$$$p_2 = max\{p_1\} = 1,$$$$
$$$$p_3 = max\{p_1,p_2\} = 1,$$$$
$$$$p_4 = max\{p_1,p_2,p_3\} = 1.$$$$