RL Bite: Bellmans Equations and Value Functions

Value Based Reinforced Learning Link to heading In value based Reinforced Learning we learn a Value Function: $$ V_{\pi}(s) = E_{\pi}[G_0|s_0 = s] = E_{\pi}[\sum_{t=0}^T \gamma^t r_t|s_0 = s] $$ $G_t$ is the Total Return at time t, this is just the sum of Rewards an Agent gets walking the trajectory T (fancy name but this is just a sequence of actions the agent takes) $\gamma^t$ is the Discount…