Related papers: ColCOS$\Phi$: A Multiple Pheromone Communication S…
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…
Flocking behavior of multiple agents can be widely observed in nature such as schooling fish and flocking birds. Recent literature has proposed the possibility that flocking is possible even only a small fraction of agents are informed of…
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…
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…
Swarms of robots will revolutionize many industrial applications, from targeted material delivery to precision farming. Controlling the motion and behavior of these swarms presents unique challenges for human operators, who cannot yet…
This paper introduces collaborating robots which provide the possibility of enhanced task performance, high reliability and decreased. Collaborating-bots are a collection of mobile robots able to self-assemble and to self-organize in order…
Collective decision-making is a widespread phenomenon in both biological and artificial systems, where individuals reach a consensus through social interactions. While traditional models of opinion dynamics and contagion focus on pairwise…
We have previously shown how to socially integrate a fish robot into a group of zebrafish thanks to biomimetic behavioural models. The models have to be calibrated on experimental data to present correct behavioural features. This…
Despite living in an increasingly connected world, social isolation is a prevalent issue today. While social robots have been explored as tools to enhance social connection through companionship, their potential as asynchronous social…
In this paper we propose DeepSwarm, a novel neural architecture search (NAS) method based on Swarm Intelligence principles. At its core DeepSwarm uses Ant Colony Optimization (ACO) to generate ant population which uses the pheromone…
Formal modelling of Multi-Agent Systems (MAS) is a challenging task due to high complexity, interaction, parallelism and continuous change of roles and organisation between agents. In this paper we record our research experience on formal…
Conversational Swarm Intelligence (CSI) is a new method for enabling large human groups to hold real-time networked conversations using a technique modeled on the dynamics of biological swarms. Through the novel use of conversational agents…
This research presents a multi-robot system for inpatient care, designed using swarm intelligence principles and incorporating wearable health sensors, RF-based communication, and AI-driven decision support. Within a simulated hospital…
We investigate to what extent the interaction dynamics of a population of wild house mouse (Mus musculus domesticus) in their environment can be explained by a simple stochastic model. We use a Markov chain model to describe the transitions…
In collective motion, perceptually-limited individuals move in an ordered manner, without centralized control. The perception of each individual is highly localized, as is its ability to interact with others. While natural collective motion…
Swarm User Interfaces allow dynamic arrangement of user environments through the use of multiple mobile robots, but their operational range is typically confined to a single plane due to constraints imposed by their two-wheel propulsion…
The importance of swarm robotics systems in both academic research and real-world applications is steadily increasing. However, to reach widespread adoption, new models that ensure the secure cooperation of large groups of robots need to be…
Better understanding the natural world is a crucial task with a wide range of applications. In environments with close proximity between humans and animals, such as zoos, it is essential to better understand the causes behind animal…
Nature evolves creatures with a high complexity of morphological and behavioral intelligence, meanwhile computational methods lag in approaching that diversity and efficacy. Co-optimization of artificial creatures' morphology and control in…
Precisely how ecological factors influence animal social structure is far from clear. We explore this question using an agent-based model inspired by the fission-fusion society of Spider monkeys (Ateles spp). Our model introduces a…