In the paper Learning to predict by the methods of temporal differences (p. 15), the weights in the temporal difference learning are updated as given by the equation $$ \Delta w_t = \alpha \left(P_{t+1} - P_t\right) \sum_{k=1}^{t}{\lambda^{t-k} \nabla_w P_k} \tag{4} \,.$$ When $\lambda = 0$, as in TD(0), how does the method learn? As it appears, with $\lambda = 0$, there will never be a change in weight and hence no learning.
Am I missing anything?