a strong limitation on the actions an agent can select, and thus, it impacts directly on the Q-values obtained for that specific state.

In a certain state, only a handful of possible actions are allowed and the agent has to establish which of those actions provide the best way to reach the maximum goal. This translates to the agent having a very small Q-value per action, as the allowed actions do not always comprise on the best ones. We illustrate this behavior on the readings of Figure \[fig:readingsExample\] (a). This is especially impacted by the competitive characteristic of the game. The agent’s next action will not be impacted only by its own previous action, but by the combined impact of the actions of its opponents.

Evaluating them alone in the Chef’s Hat competitive scenario, thus, give us a very poor reading of the game context, as it only represents how that specific action has the highest probability, among all the allowed actions, to reach the final state. It does not carry any information about how this action was impacted by the previous ones. The same can be said by the confidence values, as they are a direct transformation of the 