Think of it as how often you need the agent to make decisions. Sometimes you need to make decisions very frequently (e.g. if your system dynamics are fast) and sometimes not. Could be viewed as the equivalent of a controller rate.
The smaller ts is, the more frequently the agent will make decisions, but that will make training much slower. On the other hand, if ts is large, training may progress faster, but depending on your system it may not converge.
Hope this helps
