Initialization of the population in Evolutionary Computation algorithms is an issue of ongoing research. Proper initialization may help the algorithm to explore the search space more efficiently and detect better solutions. In this paper, the Nonlinear Simplex Method is used to initialize the swarm of the Particle Swarm technique. Experiments for several well-known benchmark problems imply that...

Emergent behaviors of collective intelligence systems, exemplified by swarm model, have attracted broad interests in recent years. However, current research mostly stops at observational interpretations and qualitative descriptions of emergent phenomena, and is essentially short of quantitative analysis and evaluation. In this paper, we conduct a quantitative study on the emergence of swarm mod...

This paper exhibits a short-run correspondence method appropriate for swarm versatile robots application. Infrared is utilized for transmitting and accepting information and obstruction location. The infrared correspondence code based swarm signaling is utilized for an independent versatile robot communication system in this research. A code based signaling system is developed for transmitting ...

Swarm robotics is an innovative approach to the control and coordination of a large number of multi-agent systems that use naturally inspired swarm intelligent methods to perform a task through emergent behaviors. A swarm based approach can decrease the complexity and the cost of designing a cooperative multi-robot system. This paper proposes a general engineering approach to develop a robotic ...

For a decade swarm Intelligence is concerned with the design of intelligent systems by taking inspiration from the collective behaviors of social insects. Swarm Intelligence is a successful paradigm for the algorithm with complex problems. This paper focuses on the procedure of most successful methods of optimization techniques inspired by Swarm Intelligence: Ant Colony Optimization (ACO) and P...

This paper presents the novel use of the Neural-endocrine architecture for swarm robotic systems. We make use of a number of behaviours to give rise to emergent swarm behaviour to allow a swarm of robots to collaborate in the task of foraging. Results show that the architecture is amenable to such a task, with the swarm being able to successfully complete the required task.

In this work, we introduce a swarm robotic system, called a swarm-bot. A swarm-bot is a self-assembling and self-organizing artifact composed of a swarm of s-bots, mobile robots with the ability to connect to/disconnect from each other. In particular, we address the problem of synthesizing controllers for the swarm-bot using Artificial Evolution. We describe the motivation behind the choice of ...

Robotic swarm behavior is usually demonstrated using groups of robots, in which each robot in the swarm must possess full mobile capabilities, including the ability to control both forward and reverse motion as well as directional steering. Such requirements place severe constraints on the cost and size of the individual robots (swarmers), limiting the number of units and constraining the overa...

We posit that swarm intelligence can be applied to effectively address requirements engineering problems. Specifically, this paper demonstrates the applicability of swarm intelligence to the requirements tracing problem using two techniques: a simple swarm algorithm and a pheromone swarm algorithm. The techniques have been validated using two real-world datasets from two problem domains. The si...

Swarm robotic systems can offer many advantages including robustness, flexibility and scalability. However one of the issues relating to overall swarm performance that needs to be considered is hardware variations inherent in the implementation of individual swarm robots. This variation can bring behavioral diversity within the swarm, resulting in uncontrollable swarm behaviors, low efficiency,...