In all other cases and intermediate timesteps, the payoff is 0. Because of the high dimensional search space introduced due to brushstrokes, we use Proximal Policy Optimization (PPO)<cite> (Schulman et al. 2017)</cite> for optimizing the weights of sender and receiver agents.