Fatigue behavior as an optimal allocation strategy for limited resources
Mental fatigue alters behavior in diverse and sometimes counter-intuitive ways. Could this be explained by the optimal allocation of limited cognitive resources? We consider that cognitive control allows to obtain more rewards from the environment, and that it gives rise to fatigue, which impedes future ability for the agent to gain rewards. Under those hypotheses, we formulated an optimal computational agent with a control allocation policy that maximizes future rewards, with two scenarios : limited resources that do not allow for more control exertion after a limit has been reached, or acc