Comparing Collective Foraging With Interactions Inspired by Pheromones and Sonar

Author(s):  
Aidan J. Bradley ◽  
Masoud Jahromi Shirazi ◽  
Nicole Abaid

Abstract Communication inspired by animals is a timely topic of research in the modeling and control of multi-agent systems. Examples of such bio-inspired communication methods include pheromone trails used by ants to forage for food and echolocation used by bats to orient themselves and hunt. Source searching is one of many challenges in the field of swarm robotics that tackles an analogous problem to animals foraging for food. This paper seeks to compare two communication methods, inspired by sonar and pheromones, in the context of a multi-agent foraging problem. We explore which model is more effective at recruiting agents to forage from a found target. The results of this work begin to uncover the complicated relationship between sensing modality, collective tasks, and spontaneous cooperation in groups.

2014 ◽  
Vol 39 (9) ◽  
pp. 1431-1438 ◽  
Author(s):  
Xiao-Yuan LUO ◽  
Shi-Kai SHAO ◽  
Xin-Ping GUAN ◽  
Yuan-Jie ZHAO

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Hong Zhou ◽  
Yu-Zhen Qin ◽  
Kuo Feng ◽  
Wen-Shan Hu ◽  
Zhi-Wei Liu

This paper investigates the consensus tracking problem for second-order multi-agent systems without/with input delays. Randomized quantization scheme is considered in the communication channels, and impulsive consensus tracking algorithms using position-only information are proposed for the consensus tracking of multi-agent systems. Based on the algebraic graph theory and stability theory of impulsive systems, sufficient and necessary conditions for consensus tracking are studied. It is found that consensus tracking for second-order multi-agent systems without/with input delays can be achieved by appropriately choosing the sampling period and control gains which are determined by second/third degree polynomials. Simulations are performed to validate the theoretical results.


AI Magazine ◽  
2018 ◽  
Vol 39 (4) ◽  
pp. 29-35
Author(s):  
Christopher Amato ◽  
Haitham Bou Ammar ◽  
Elizabeth Churchill ◽  
Erez Karpas ◽  
Takashi Kido ◽  
...  

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University’s Department of Computer Science, presented the 2018 Spring Symposium Series, held Monday through Wednesday, March 26–28, 2018, on the campus of Stanford University. The seven symposia held were AI and Society: Ethics, Safety and Trustworthiness in Intelligent Agents; Artificial Intelligence for the Internet of Everything; Beyond Machine Intelligence: Understanding Cognitive Bias and Humanity for Well-Being AI; Data Efficient Reinforcement Learning; The Design of the User Experience for Artificial Intelligence (the UX of AI); Integrated Representation, Reasoning, and Learning in Robotics; Learning, Inference, and Control of Multi-Agent Systems. This report, compiled from organizers of the symposia, summarizes the research of five of the symposia that took place.


2015 ◽  
Vol 237 ◽  
pp. 183-188
Author(s):  
Mirosław Mrozek

Multi-agent systems are used mainly in IT solutions and control groups of robots. From the point of view of classical control architectures, they are a kind of distributed systems in which nodes perform advanced algorithms, usually associated with the technology of artificial intelligence, and they can be considered as agents. The article describes the multi-agents control system of objects of uniaxial movements. An example of such a system to control a repository with movable racks with electric motors is presented. Each rack acts as an agent through the implemented control of the resources of embedded microcontrollers. Such a system provides high quality control, guaranteeing long-lasting, trouble-free operation while maintaining the safety of both service and stored items.


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