mood readings of each of its opponents. Figure \[fig:moodyFramework\] illustrates the entire processing flow of the *Moody framework* , illustrating how the Player 1 obtains its mood reading and the e-mood reading for one opponent.

![image](MoodyFramework.png){width="1.5\columnwidth"}

Experiments
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We perform two rounds of experiments in order to address our two main research questions: 1) How the mood readings provide the understanding of the agents’ behavior on the Chef’s Hat game; 2) How close is the representation of the mood estimated by an agent about its opponents from the real mood of each of these opponents.

Mood vs Confidence
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Our first experiment aims to demonstrate the capabilities of the *Moody framework* to describe the performance of an agent when making actions on the Chef’s Hat game. To do so, we set up one game and put a DQL-based, a PPO-based and 2 dummy agents to play against each other. We collect the confidence and mood values for the DQL and PPO agents and exhibit how they describe each other’s behavior during the game. We also collect and exhibit the estimated confidence and estimated mood that each of these two agents calculated about each other. To illustrate further the capabilities of 