# Swarm Robotics: A Perspective on the Latest Reviewed Concepts and Applications
## 5 Basic Behaviors and Tasks in Swarm Robotics
### Aggregation  
Aggregation is a technique where single robots gather together to achieve tasks, for instance, collective movement or exchange of information. This technique permits swarm agents to get spatially nearby in a particular region to each other for more interaction. Aiming to demonstrate the aggregation dynamics, [PERSON] et al. [95] concentrate the investigation on the self-organized aggregation of swarm-robot systems. According to the authors, the goal was to survey the prelude of \"informed robots\" and examine the amount of these agents are required to conduct the aggregation development regarding a predetermined area among those accessible in ambiance. They investigate the aggregation procedure with informed robots in three situations: two are morphologically symmetric and an asymmetric scenario. This research's main collaboration is to prove the result of the insertion of a small part of informed robots in both ambiances: symmetric and asymmetric ambiances. In symmetric ambiances, agents conduct the aggregation method to investigate selected areas; in the asymmetric ambiance, informed robots can change natural choices in the majority denoted area and persuade the swarm to gather on minimum select areas. The authors demonstrate detailed experiments to investigate how the procedure can foretell the dynamics noticed with a swarm in symmetric situations. [PERSON] et al. [96] investigate the Minkowski distance function in self-organized research aggregations inside swarm robotics systems. The authors developed an aggregation technique named DM-KNN, supported by the Minkowski distance function. The authors also say the employment of such a function conducts an essential advance in the aggregation efficiency when confronted with a preceding aggregation procedure. The authors analyze the efficiency of their technique with that DM-KNN technique using the AMBR metric. Subsequently, they study the efficiency of the two techniques by considering the swarm dispersion capacity they intend to minimize. Experiments indicate the suggestedaggregation technique surpasses the performance in contrast to the DW-KNN proposal. [PERSON] et al. [97] proposed a fuzzy-based self-organizing aggregation approach. In the developed technique, swarm agents assess their controlled sensor input by norms of fuzzy logic and exhibit aggregation behavior with the proposed approach. Simultaneously, swarm agents either own the facility to avoid obstructions in a restricted area with this procedure. Swarm agents identify nearby robots, make choices, and show aggregation behaviors. The authors explain the proposed method employs fuzzy logic controllers to rate restricted sensor data. Organized experiments were employed on several swarm robots with diverse areas dimensions. Furthermore, the noise was employed on the sensor input to investigate the fuzzy logic's efficiency supported the self-organizing aggregation procedure. [PERSON] and [PERSON] [98] introduce a decentralized technique for swarm aggregation. This technique simplifies tasks, whereas the robots practice local decision-making. The authors say this research's first goal is to arrange steady gathers of a swarm employing exclusive local experience and no interaction between robots. A theoretical study of the suggested procedure is shown encouraged in the concept of switched systems. Computational experiments are performed to prove aggregates' stability in the closeness of broad barriers and outward perturbations. Moreover, the authors describe an implementation of the suggested controller in an authentic process using examinations on the swarm of distinctive microbots. The proposed method lacking communication indicates comparable performance compared to previous swarm aggregation methods employing global and local iterations. Distributed and Reinforcement Learning  
Reinforcement learning is a supported method where agents that can be in a group of conditions and can perform a specified group of activities, collect feedback on the outcomes of their actions, over an award.