Reinforcement Learning, Deep Learning, Machine Learning, Neural Networks, Algorithms.
The action-value function is denoted by Q(s,a) and is defined as the expected cumulative reward that an agent can receive starting from state s, taking action a, and following the current policy. The value function is estimated using past experiences and updated through iterative learning methods,