# A Swarm-Based Approach to Generate Challenging Mazes
## 2 Swarm Intelligence Algorithms and Their Applications
### Selected Applications of Swarm Algorithms  
The algorithms that are based on swarm behaviour are treated as promising tools for many applications, owing to their simple implementation, short computational time, and effective mechanisms that prevent the agents being stuck in their local optimum. The multiple applications of swarm intelligence also include optimization problem solving, finding the shortest route, assignments and scheduling, or object grouping. Owing to high flexibility in the adjustment to changing dimensions of solution spaces, swarm algorithms were used for solving the travelling salesman problem [29; 31]. The paper [32] presents an automated guided vehicle (AGV) control system, using the Wireless Sensor Network technology so that the vehicles can operate as mobile robots, using the swarm intelligence to coordinate vehicle operation. The algorithms based on swarm intelligence are also applied in solving the Quadratic Assignment Problem (QAP), modelling a number of such issues as the travelling salesman problem, generalised problem of graph subdivision, or the problem of finding a maximum clique [33]. Certain studies also concerned the application of swarm algorithms to tune PID controllers [34; 35; 36; 37]. Many researchers dealt with swarm-based approaches to train classifiers. In [38], particle swarm optimization and artificial bee colony were presented to train feed-forward neural network for pathological brain detection. Moreover, [PERSON] et al. [39] employed real-coded biogeography-based optimization to find the optimal weights and biases of feedforward neural network optimization. In turn, in [40], a classification system for Alzheimer's disease, combining wavelet entropy and multilayer perceptron optimized by biogeography-based approach was developed. Some mechanisms that constitute the foundation of social structures can be used to control a colony of robots. Swarm Robotics (SR) is one of the most promising technologies intended to develop reliable, scalable, and flexible systems. Swarm intelligence mechanisms have been applied in many various tasks performed by a group of autonomous robots that are capable of moving and interacting with their environment, without a centralised control system [41]. For example, the situation that occurs in bird flocks or schools of fish, where individuals move in the direction of a known target location, avoiding collisions, is reflected in designing robot group relocation towards the selected target. \"Foraging\" or \"area plundering\" techniques are often applied in swarm robotic systems. Robots have to collect the objects acquired from their environment and bring them back to their nest. \"Foraging\" can reflect demining and search and rescue operations. The technique can be applied for collective land exploration, cargo transportation, or decision making, as well as for the purpose of testing the influence of disturbances on a group of robots [42]. In [43], swarm intelligence has been proposed for the management of autonomous and independent unmanned aerial vehicles (drones). The challenges faced by fleet of drones during all operations ranging from flight control to cybersecurity are investigated. It should be noted that drones can learn on the basis of the situation in which they find themselves. Besides, swarm intelligence mechanisms are being applied in Internet of Things applications, modern data networking, the efficient management of large-scale ad-hoc networks (wireless sensor networks) and so on [44; 45]. In [46], comprehensive reviews for swarm intelligence based routing protocols for Wireless Sensor Networks were provided. In summary, swarm-based algorithms are very useful in a diverse range of optimization tasks in real applications. A broad overview of various applications is presented in [47]. It should be mentioned that many issues exist concerning these approaches [48]. One of the challenges is the appropriate design and implementation of their all procedures.