Alignment as Biological Inspiration for Control of Multi Agent Systems

2014 ◽  
Author(s):  
Hossein Rastgoftar ◽  
Suhada Jayasuriya
Keyword(s):  
Deformable Body ◽  
Multi Agent Systems ◽  
Individual Agent ◽  
Peer Communication ◽  
Agent Systems ◽  
Biological Inspiration ◽  
Local Perception ◽  
Individual Perception ◽  
Multi Agent ◽  
Straight Lines

In this paper, we develop a framework for evolution of a multi agent systems (MAS) under local perception. The idea of this paper comes from natural biological swarms where agents adjust their behavior based on individual perception of the behavior of its neighbors. Most available engineered swarms rely on local communication where an individual agent needs exact state information of its adjacent agents to evolve. We consider agents of a MAS to be particles of a continuum (deformable Body) transforming under a homogenous mapping. Homogenous transformations have the property that two crossing straight lines in an initial configuration translate as two different crossing straight lines. We will consider this feature of homogenous mappings to show how certain desired objectives can be achieved by agents of a swarm by preserving alignment among nearby agents. We show that evolution of a MAS under this alignment strategy can be achieved where agents don’t need to know the exact positions of the adjacent agents nor do they need peer to peer communication.

scholarly journals Multi-agent systems for cooperative ITS

2021 ◽  
pp. 42-50
Author(s):  
Roman Dushkin
Keyword(s):  
Transport Systems ◽  
Transport Sector ◽  
Multi Agent Systems ◽  
Automated Vehicles ◽  
Intelligent Transport Systems ◽  
Individual Agent ◽  
Intelligent Transport ◽  
Agent Systems ◽  
Interacting Agents ◽  
Multi Agent

This article presents an original perspective upon the problem of creating intelligent transport systems in the conditions of using highly automated vehicles that freely move on the urban street-road networks. The author explores the issues of organizing a multi-agent system from such vehicles for solving the higher level tasks rather than by an individual agent (in this case – by a vehicle). Attention is also given to different types of interaction between the vehicles or vehicles and other agents. The examples of new tasks, in which the arrangement of such interaction would play a crucial role, are described. The scientific novelty is based on the application of particular methods and technologies of the multi-agent systems theory from the field of artificial intelligence to the creation of intelligent transport systems and organizing free-flow movement of highly automated vehicles. It is demonstrated the multi-agent systems are able to solve more complex tasks than separate agents or a group of non-interacting agents. This allows obtaining the emergent effects of the so-called swarm intelligence of the multiple interacting agents. This article may be valuable to everyone interested in the future of the transport sector.

scholarly journals DELIBERATIVE EVOLUTION IN MULTI-AGENT SYSTEMS

2001 ◽  
Vol 11 (05) ◽  
pp. 559-581 ◽  
Author(s):  
F. M. T. BRAZIER ◽  
C. M. JONKER ◽  
J. TREUR ◽  
N. J. E. WIJNGAARDS
Keyword(s):  
Multi Agent Systems ◽  
Agent Architecture ◽  
Individual Agent ◽  
New Agents ◽  
Agent Model ◽  
Development Method ◽  
Agent Systems ◽  
Generic Agent ◽  
Multi Agent ◽  
Material Process

Evolution of automated systems, in particular evolution of automated agents based on agent deliberation, is the topic of this paper. Evolution is not a merely material process, it requires interaction within and between individuals, their environments and societies of agents. An architecture for an individual agent capable of (1) deliberation about the creation of new agents, and (2) (run-time) creation of a new agent on the basis of this, is presented. The agent architecture is based on an existing generic agent model, and includes explicit formal conceptual representations of both design structures of agents and (behavioural) properties of agents. The process of deliberation is based on an existing generic reasoning model of design. The architecture has been designed using the compositional development method DESIRE, and has been tested in a prototype implementation.

scholarly journals Agent, Behaviour, Trace, Repeat: Understanding the Cognitive Processes Involved in Human Stigmergic Coordination

2021 ◽  
Author(s):  
Sabine Topf ◽  
Maarten Speekenbrink
Keyword(s):  
Cognitive Processes ◽  
Future Research ◽  
Shared Environment ◽  
Multi Agent Systems ◽  
Causal Inferences ◽  
Individual Agent ◽  
Intentional Communication ◽  
Agent Systems ◽  
Multi Agent ◽  
Exploration Exploitation

Stigmergy refers to the coordination of agents via artifacts of behaviours (behavioural traces) in the shared environment. Whilst primarily studied in biology and computer science/robotics, stigmergy underlies many human indirect interactions, both offline (e.g., trail building) and online (e.g., development of open-source software). In this review, we provide an introduction to stigmergy and emphasise how and where human stigmergy is distinct from animal or robot stigmergy, such as intentional communication via traces and causal inferences from the traces to the causing behaviour. Cognitive processes discussed on the agent level include attention, motivation, meaning and meta-cognition, as well as emergence/immergence, iterative learning and exploration/exploitation at the interface of individual agent and multi-agent systems. Characteristics of one-agent, two-agent and multi-agent systems are discussed and areas for future research highlighted.

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