agent about its opponents from the real mood of each of these opponents. To answer these questions we perform a series of experiments where different agents play a series of games using the Chef’s Hat simulation environment. We explain how the agents’ own assessment of the opponents’ actions impacts the performance explanation. Also, to better understand the impact of the *Moody framework* on the XAI community, we discuss the effect of our self-evaluation in competitive scenarios and how they can provide a closed-world representation of the entire game.

Game Mechanics and Agents Implementation
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The Chef’s Hat Card Game
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The game setup which we used as an environment for our artificial agents is the Chef’s Hat card game [@barros2020food]. Chef’s Hat as a game provides a controllable action-perception cycle, where each player can only perform a restricted set of actions. This in turn allows each player to behave as organically as possible, and allows us to directly measure the impact of each action within the naturally-controllable real-world scenario.

Chef’s Hat is a 4-player round-based card game, where each person has a restaurant-context role (Chef, Sous-Chef, Waiter or Dishwasher), that is updated after each game based on the order of 