Latest methodlogy and Innovations in swarm intelligence
Swarm intelligence is the discipline that deals with the study of self-organizing processes both in nature and in artificial systems. Researchers in ethology and animal behaviour have proposed a number of models to explain interesting aspects of collective behaviours such as movement coordination, shape-formation or decision making. Recently, algorithms and methods inspired by these models have been proposed to solve difficult problems in many domains. Among these, it is worth mentioning ant colony optimization (ACO) and particle swarm optimization (PSO), focusing respectively on discrete and continuous optimisation problems. Also, Swarm robotics represents another application of techniques derived from swarm intelligence for the design of collaborative multi-robot systems featuring enhanced efficiency, robustness and scalability.
Topics of interest are:
- Behavioural models of social insects or other animal societies that can stimulate new algorithmic approaches.
- Theoretical and empirical and research in swarm intelligence.
- Application of swarm intelligence methods (e.g., ant colony optimisation or particle swarm optimisation) to real-world problems.
- Theoretical and experimental research in swarm robotics systems.
Humanoid Robotics: A New Development
A humanoid robot is a robot that not only resembles human's physical attributes especially one head, a torso, and two arms but also should have the capability to communicate with humans and other robots, interpret information, and perform limited activities according to the user’s input. Humanoid robots are equipped with sensors and actuators. These robots are typically pre-programmed for determined specific activities: Humanoid motion planning and control, Humanoid grasping and manipulation, Learning and imitation strategies for humanoids, Software and hardware architectures, Perception and sensing for humanoids
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International journal of swarm intelligence and evolutionary computation