Novel Learning Algorithms for Efficient Mobile Sink Data Collection Using Reinforcement Learning in Wireless Sensor Network

Table 3

Representation of RL based clustering elements.

State	Set of neighbouring cluster S = (0, 1, 2...n). A state represents neighbouring cluster head CH which can be selected as [9–11, 24, 37]
Action	Set of actions in state A = (0, 1, 2...n). Here, an action selects cluster head CH and compute rewards [9, 11, 24, 37]
Reward	The computation of cumulative reward is based upon the selection of action and state [9, 11, 24, 37]