Fig. 1From: Reinforcement learning in local energy marketsConvergence of the learning strategy with change in rec parameter for a single household. Figure 1 refers to the convergence of the strategy to a single price point for different values of rec parameter for a particular household. For rec = 0,01, the strategy demonstrates a slow convergence. As the rec is decreased to 0,0125, the strategy enters the moderate convergence time tc. Above rec = 0,02, the strategy enters the fast convergence mode. It can be observed that the faster rate of convergence also drives the strategy to a lower price point. As a result, the faster rate of convergence provides a better gain in the short term by settling faster on a particular price but it also increases the risk of choosing a price which may be lower than the average MCP which may lead to losses in the long termBack to article page