# Multi-Agent System for Emulating Personality Traits Using Deep Reinforcement Learning +
## 4 Discussion  
Based on the findings, it can be confidently asserted that the individual personality traits exhibited by the agents within each team have a substantial influence on the overall dynamics of the group, including its operational efficiency and the speed with which they achieve their objectives, such as escaping. This underscores the critical importance of the reward functions employed and their configuration, as they have the capacity to accurately mirror and replicate the diverse range of traits and behaviors observed in real-life scenarios. In essence, the design and implementation of these reward structures have the potential to faithfully emulate the complexities of human traits and behaviors through logical frameworks. In our analysis, we have observed intriguing trends regarding the performance of agents based on their personality traits. Particularly noteworthy is the efficiency and effectiveness exhibited by agreeable agents, who demonstrate a remarkable propensity for cooperation and swift problem-solving. These individuals, characterized by their affable and cooperative nature, seamlessly navigate through challenges, leveraging their strong interpersonal skills to foster collaboration within the team dynamic. On the other side, introverted agents, while equally effective in their problem-solving capabilities, tend to approach tasks at a more deliberate pace. Their cautious and introspective nature often translates into a methodical approach to problem-solving, resulting in slower but effective progress through the ER challenges. Moreover, our findings reveal intriguing dynamics when teams are composed of agents representing a spectrum of personality traits. In such scenarios, we have observed challenges in collaboration, particularly during the initial stages of engagement. The diverse array of personality traits within the team dynamic can lead to discrepancies in communication styles, decision-making processes, and conflict-resolution strategies, posing initial obstacles to seamless cooperation. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Traits** & **HiDAC Behavior** & **Our System Behavior** \\ \hline \multirow{3}{*}{Openness} & As Openness increases, the number of places they explore & The mean escape time of the \\  & increases, and thus, they leave the building later. & Openness agents team is \\  & & increased (+25\%). \\ \hline \multirow{3}{*}{Extroverts and Introverts} & The Extroverts approach the attraction point in a shorter & The Extroverts show better times \\  & time. In addition, when there are other agents blocking & of escaping (+5\%), as well as \\  & their way, they tend to push them to reach their goal. & higher push action metrics \\  & The shortest time is achieved when Conscientiousness and & The agents that have high \\  & Agreeableness are the highest. The result is expected as & Conscientiousnessness and \\  & agreeable and conscientious individuals are more patient, & Agreeableness are quicker than \\  & they do not push each other, and are always predictable, & the ones with lower (+5\% and \\  & as they prefer the right side to move on. Also, the longest & +4\%, respectively) and lower \\  & time is obtained when both values are minimal. & push actions (\(>-25\%\)) \\ \hline \multirow{3}{*}{Neurotic} & Agents that are Neurotic with less Conscientiousness tend & The Neurotic agents are quicker \\  & to panic more, pushing other agents forcing their way & to finish the room (+5\%) though \\  & through the crowd, and rushing to the door. & less successful (\(-55\%\)). \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Tested scenarios used for result comparison and evaluation. These insights underscore the intricate interplay between individual personality traits and collective team dynamics within the multi-agent environment. By understanding and leveraging these nuances, we can tailor strategies and interventions to optimize team performance, fostering a cohesive and synergistic approach to problem-solving within the ER setting.