For a decade swarm Intelligence, an artificial intelligence discipline, is concerned with the design of intelligent multi-agent systems by taking inspiration from the collective behaviors of social insects and other animal societies. They are characterized by a decentralized way of working that mimics the behavior of the swarm. Swarm Intelligence is a successful paradigm for the algorithm with ...

In this paper we described the hardware architecture of an inexpensive, heterogeneous, mobile robot swarm, designed and developed at RISC lab, University of Bridgeport. Each UB robot swarm is equipped with sensors, actuators, control and communication units, power supply, and interconnection mechanism. Robot swarms have become a new research paradigm in the last ten years offering novel approac...

While the robot is inmotion, path planning should follow the three aspects: (1) acquire the knowledge from its environmental conditions. (2) determine its position in the environment and (3) decision-making and execution to achieve its highest-order goals. The present research work aims to develop an efficient particle swarm optimizationbased path planner of an autonomous mobile robot. In this ...

Swarm robots are special multi-robots and usually considered being controlled with swarm intelligence-basedmethod to complete some assigned complex tasks (Dorigo and Sahin, 2004). Similar to the biological counterparts in nature, swarm intelligence among such artificial system is emerged from local interactions between individual robots or individual robot and its environment (Beni, 2005; Şahin...

Watermark perceptibility and robustness must be ensured in order to enhance the practicality of digital watermarking. Taking human visual system characteristics into account fully, a particle swarm optimization method based on multi-wavelet digital watermarking is proposed. It utilizes Sa4 multiwavelet to embed digital watermark, chooses intermediate frequency in embedding digital watermark ada...

In this paper we propose a new distributed double guided hybrid algorithm combining the particle swarm optimization (PSO) with genetic algorithms (GA) to resolve maximal constraint satisfaction problems (Max-CSPs). It consists on a multi-agent approach inspired by a centralized version of hybrid algorithm called Genetical Swarm Optimization (GSO). Our approach consists of a set of evolutionary ...

Interactive Multi-Objective Optimisation is an increasing field of evolutionary and swarm intelligence-based algorithms. By involving a human decision, a set of relevant non-dominated points can often be acquired at significantly lower computational costs than with a posteriori algorithms. A rarely addressed issue in interactive optimisation is the design of efficient user interfaces and the ap...

The work reported in this paper proposes ‘Intelligent Agents’, a Swarm-Array computing approach focused to apply autonomic computing concepts to parallel computing systems and build reliable systems for space applications. Swarm-array computing is a robotics a swarm robotics inspired novel computing approach considered as a path to achieve autonomy in parallel computing systems. In the intellig...

Swarm coordination and formation control designs focus on multi-agent dynamic system behavior and aim to achieve desired coordinated behavior or predefined geometric shape. They utilize techniques from the control theory and graph theory literature. On the other hand, adaptive control theory is concerned with uncertainties in the system dynamics, and has structured frameworks for various types ...

Inspired by the phenomenon of symbiosis in natural ecosystems a multi-swarm cooperative particle swarm optimizer (MCPSO) is proposed as a new fuzzy modeling strategy for identification and control of non-linear dynamical systems. In MCPSO, the population consists of one master swarm and several slave swarms. The slave swarms execute particle swarm optimization (PSO) or its variants independentl...