Discovering the New Advances on Swarm Intelligence for the Future Generation
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
The journal invites different types of articles including original research article, review articles, short note communications, case reports, Editorials, letters to the Editors and expert opinions & commentaries from different regions for publication.
A standard editorial manager system is utilized for manuscript submission, review, editorial processing and tracking which can be securely accessed by the authors, reviewers and editors for monitoring and tracking the article processing. Manuscripts can be uploaded online at Editorial Tracking System ((https://www.longdom.org/editorial-tracking/index.php or forwarded to the Editorial Office at https://www.longdom.org/swarm-intelligence-evolutionary-computation.html
How we work:
- After submission, an acknowledgement with manuscript number is sent to the corresponding author within 7 working days.
- A 21 day window time frame is allotted for peer-review process wherein multiple experts are contacted.
- Author proof is generated within 7 working days after the acceptance decision.
Benefits on Publication:
Open Access: Permanent free access to your article upon publication ensures extensive global reach and readership.
Easy Article Sharing: Our open access enables you to share your article directly with colleagues through email and on social media via a single link, permitting third party reuse with appropriate citation in addition to the retention of content copyright by the author.
Global Marketing: Through promotion in a targeted global email announcement or press release, your article will be seen by thousands of the top-most thought-leaders in your field.
Color Art: In a world of black & white journal articles, high-quality full-color images make your article stand out from the crowd and tell a complete story, increasing readers and citations.
Social Media Exposure: Extended reach for your article through links on Twitter accounts provides maximum visibility worldwide.
Reprints: Distribute your work to colleagues and at conferences as we provide hard copy color reprints of your article on order.
International journal of swarm intelligence and evolutionary computation