scholarly journals Determining asymptotically large population sizes in insect swarms

2014 ◽  
Vol 11 (99) ◽  
pp. 20140710 ◽  
Author(s):  
James G. Puckett ◽  
Nicholas T. Ouellette
Keyword(s):  
Group Dynamics ◽  
Large Population ◽  
Environmental Cues ◽  
Multi Agent Systems ◽  
Strong Constraint ◽  
Agent Systems ◽  
Self Organized ◽  
Large Numbers ◽  
Population Sizes ◽  
Multi Agent

Social animals commonly form aggregates that exhibit emergent collective behaviour, with group dynamics that are distinct from the behaviour of individuals. Simple models can qualitatively reproduce such behaviour, but only with large numbers of individuals. But how rapidly do the collective properties of animal aggregations in nature emerge with group size? Here, we study swarms of Chironomus riparius midges and measure how their statistical properties change as a function of the number of participating individuals. Once the swarms contain order 10 individuals, we find that all statistics saturate and the swarms enter an asymptotic regime. The influence of environmental cues on the swarm morphology decays on a similar scale. Our results provide a strong constraint on how rapidly swarm models must produce collective states. But our findings support the feasibility of using swarms as a design template for multi-agent systems, because self-organized states are possible even with few agents.

An overview of search strategies in distributed environments

2013 ◽  
Vol 29 (3) ◽  
pp. 281-313 ◽  
Author(s):  
E. Del Val ◽  
M. Rebollo ◽  
V. Botti
Keyword(s):  
Dynamic Environments ◽  
System Structure ◽  
Search Process ◽  
Global Information ◽  
Distributed Environments ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Service Oriented ◽  
Multi Agent ◽  
Proper Performance

AbstractDistributed systems are populated by a large number of heterogeneous entities that join and leave the systems dynamically. These entities act as clients and providers and interact with each other in order to get a resource or to achieve a goal. To facilitate the collaboration between entities, the system should provide mechanisms to manage the information about which entities or resources are available in the system at a certain moment, as well as how to locate them in an efficient way. However, this is not an easy task in open and dynamic environments where there are changes in the available resources and global information is not always available. In this paper, we present a comprehensive vision of search in distributed environments. This review not only considers the approaches of the peer-to-peer area, but also the approaches from three more areas: service-oriented environments, multi-agent systems, and complex networks. In these areas, the search for resources, services, or entities plays a key role for the proper performance of the systems built on them. The aim of this analysis is to compare approaches from these areas taking into account the underlying system structure and the algorithms or strategies that participate in the search process.

The M3 Architecture for Smart Spaces

2017 ◽  
pp. 29-48
Keyword(s):  
Theoretical Background ◽  
Smart Environments ◽  
Multi Agent Systems ◽  
Smart Spaces ◽  
Generic Properties ◽  
Agent Systems ◽  
Space Design ◽  
Service Oriented ◽  
Multi Agent ◽  
Generic Design

In accordance with the previous chapter, a particular class of smart environments is created by Smart Spaces, where many devices participate using information-driven and ontology-oriented interaction. In this case, a smart space is developed based on models from multi-agent systems and knowledge manipulation technologies from the Semantic Web. In this chapter, we consider this particular approach for creating such smart environments. The M3 architecture (multidevice, multivendor, multidomain) aims at development of smart spaces that host advanced service-oriented applications. We introduce the theoretical background of the M3 architecture in respect to its open source implementation—the Smart-M3 platform. The latter forms a technology for creating M3-based smart spaces (M3 spaces) as heterogeneous dynamic multi-agent systems with multi-device, multi-vendor, multi-domain devices and services. We further consider the concept models of space computing that enable the studied class of smart spaces, derive the generic properties that an M3 space design requires, and describe the basic software components of M3 architecture that realize the generic design properties in accordance with the concept models.

Extending the JADE Framework for Semantic Peer-To-Peer Service Based Applications

2010 ◽  
pp. 18-35
Author(s):  
Agostino Poggi ◽  
Michele Tomaiuolo
Keyword(s):  
Distributed Systems ◽  
Peer To Peer ◽  
Legacy Systems ◽  
Software Framework ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Service Oriented ◽  
Multi Agent

One of the main challenges of multi-agent systems is to become the main means to support legacy systems interoperability and to make the realization of scalable distributed systems easy. In the last years, however, two technologies, peer-to-peer and service-oriented, have made an impressive progress and seem to have good chances of competing with multi-agent systems for the realization of scalable and interoperable systems. Conversely, neither of these two technologies is able to provide by themselves the autonomy and social and proactive capabilities of agents and thus the development of flexible adaptive distributed systems may be difficult. This chapter shows how JADE, one of the most known and used software framework for the development of multi-agent systems, has been extended with these technologies both to support the realization of multi-agent systems and to facilitate the interoperability with peer-to-peer and service-oriented systems.

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