Related papers: A Brief Review of Nature-Inspired Algorithms for O…
We present a new social animal inspired emotional swarm intelligence technique. This technique is used to solve a variant of the popular collective robots problem called foraging. We show with a simulation study how simple interaction rules…
Evolutionary algorithm research and applications began over 50 years ago. Like other artificial intelligence techniques, evolutionary algorithms will likely see increased use and development due to the increased availability of computation,…
Over the last few years, more and more heuristic decision making techniques have been inspired by nature, e.g. evolutionary algorithms, ant colony optimisation and simulated annealing. More recently, a novel computational intelligence…
Robotic swarms are decentralized multi-robot systems whose members use local information from proximal neighbors to execute simple reactive control laws that result in emergent collective behaviors. In contrast, members of a general…
We propose a Self-Regulated Swarm (SRS) algorithm which hybridizes the advantageous characteristics of Swarm Intelligence as the emergence of a societal environmental memory or cognitive map via collective pheromone laying in the landscape…
In the software industry, two software engineering development best practices coexist: open-source and closed-source software. The former has a shared code that anyone can contribute, whereas the latter has a proprietary code that only the…
Coordination of multi agent systems remains as a problem since there is no prominent method to completely solve this problem. Metaheuristic agents are specific implementations of multi-agent systems, which imposes working together to solve…
Natural systems often exhibit chaotic behavior in their space-time evolution. Systems transiting between chaos and order manifest a potential to compute, as shown with cellular automata and artificial neural networks. We demonstrate that…
Optimization aims at selecting a feasible set of parameters in an attempt to solve a particular problem, being applied in a wide range of applications, such as operations research, machine learning fine-tuning, and control engineering,…
Software production research is quickly evolving on two parallel approaches: conventional and bio-inspired. The bio-inspired approaches are generally developed and presented as enhancements of the conventional ones. However the conventional…
This paper proposes a new numerical optimization algorithm inspired by the strawberry plant for solving complicated engineering problems. Plants like strawberry develop both runners and roots for propagation and search for water resources…
Metaheuristic algorithms are powerful tools for global optimization, particularly for non-convex and non-differentiable problems where exact methods are often impractical. Particle-based optimization methods, inspired by swarm intelligence…
In this paper we highlight the scopes of engineering bio-inspired political systems, which are political systems based on the properties of life that self-organize the increasing complexity of human social systems. We describe bio-inspired…
Computational Intelligence algorithms have gained a lot of attention of researchers in the recent years due to their ability to deliver near optimal solutions.
The objective of this paper is to introduce an artificial intelligence based optimization approach, which is inspired from Piagets theory on cognitive development. The approach has been designed according to essential processes that an…
Inspired by biological swarms, robotic swarms are envisioned to solve real-world problems that are difficult for individual agents. Biological swarms can achieve collective intelligence based on local interactions and simple rules; however,…
This paper presents the Goat Optimization Algorithm (GOA), a novel bio-inspired metaheuristic optimization technique inspired by goats' adaptive foraging, strategic movement, and parasite avoidance behaviors.GOA is designed to balance…
We analyze algorithmic and computational aspects of biological phenomena, such as replication and programmed death, in the context of machine learning. We use two different measures of neuron efficiency to develop machine learning…
Human-swarm interaction (HSI) is an active research challenge in the realms of swarm robotics and human-factors engineering. Here we apply a cognitive systems engineering perspective and introduce a neuro-inspired joint systems theory of…
Chicken swarm optimization is a new meta-heuristic algorithm which mimics the foraging hierarchical behavior of chicken. In this paper, we describe the preprocessing of handwritten document by contrast enhancement while preserving detail…