The field of autonomous systems and swarm robotics is rapidly advancing, with a focus on developing innovative solutions for complex problems. Recent research has explored the integration of opinion dynamics into safety control frameworks, enabling collaborative decision-making and blocking-free resolution in decentralized systems. Additionally, collective decision-making strategies have been proposed, allowing swarms to adaptively determine the size of the subset required for accurate decision-making. Furthermore, researchers have investigated the use of reinforcement learning for decision-level interception prioritization in drone swarm defense, demonstrating the potential for enhanced resilience and defensive efficiency. Noteworthy papers include: Integrating Opinion Dynamics into Safety Control for Decentralized Airplane Encounter Resolution, which proposes a bio-inspired nonlinear opinion dynamics approach for guaranteeing both safety and blocking-free resolution. SubCDM: Collective Decision-Making with a Swarm Subset, which enables decisions using only a swarm subset, reducing the number of robots required for collective decision-making. Reinforcement Learning for Decision-Level Interception Prioritization in Drone Swarm Defense, which introduces a high-fidelity simulation environment for evaluating the performance of reinforcement learning agents in drone swarm defense scenarios.