Distributed Multi-Agent Systems for a Collective Construction Task based on Virtual Swarm Intelligence

2010 ◽  
Vol 1 (2) ◽  
pp. 58-79 ◽  
Author(s):  
Yan Meng ◽  
Yaochu Jin
Keyword(s):  
Swarm Intelligence ◽  
Random Search ◽  
Building Blocks ◽  
Local Area ◽  
Multi Agent Systems ◽  
Virtual Particle ◽  
Multi Agent ◽  
Bounded Area ◽  
Collective Construction ◽  
Construction Task

In this paper, a virtual swarm intelligence (VSI)-based algorithm is proposed to coordinate a distributed multi-robot system for a collective construction task. Three phases are involved in a construction task: search, detect, and carry. Initially, robots are randomly located within a bounded area and start random search for building blocks. Once the building blocks are detected, agents need to share the information with their local neighbors. A distributed virtual pheromone-trail (DVP) based model is proposed for local communication among agents. If multiple building blocks are detected in a local area, agents need to make decisions on which agent(s) should carry which block(s). To this end, a virtual particle swarm optimization (V-PSO)-based model is developed for multi-agent behavior coordination. Furthermore, a quorum sensing (QS)-based model is employed to balance the tradeoff between exploitation and exploration, so that an optimal overall performance can be achieved. Extensive simulation results on a collective construction task have demonstrated the efficiency and robustness of the proposed VSI-based framework.

Distributed Multi-Agent Systems for a Collective Construction Task based on Virtual Swarm Intelligence

2012 ◽  
pp. 308-330
Author(s):  
Yan Meng ◽  
Yaochu Jin
Keyword(s):  
Swarm Intelligence ◽  
Random Search ◽  
Building Blocks ◽  
Local Area ◽  
Multi Agent Systems ◽  
Virtual Particle ◽  
Multi Agent ◽  
Bounded Area ◽  
Collective Construction ◽  
Construction Task

In this paper, a virtual swarm intelligence (VSI)-based algorithm is proposed to coordinate a distributed multi-robot system for a collective construction task. Three phases are involved in a construction task: search, detect, and carry. Initially, robots are randomly located within a bounded area and start random search for building blocks. Once the building blocks are detected, agents need to share the information with their local neighbors. A distributed virtual pheromone-trail (DVP) based model is proposed for local communication among agents. If multiple building blocks are detected in a local area, agents need to make decisions on which agent(s) should carry which block(s). To this end, a virtual particle swarm optimization (V-PSO)-based model is developed for multi-agent behavior coordination. Furthermore, a quorum sensing (QS)-based model is employed to balance the tradeoff between exploitation and exploration, so that an optimal overall performance can be achieved. Extensive simulation results on a collective construction task have demonstrated the efficiency and robustness of the proposed VSI-based framework.

Research on applications and problem of control of swarm intelligence and robotics

2020 ◽  
Vol 25 (1) ◽  
pp. 44-50
Author(s):  
Baraniuk A.S. ◽  
Keyword(s):  
Swarm Intelligence ◽  
Future Research ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Advantages And Disadvantages ◽  
Multi Agent ◽  
And Robotics

This article provides overview of the swarm intelligence and robotics fields, main characteristics of such systems provided, their advantages and disadvantages as well as differences from other multi-agent systems. Also, main fields of application for swarm systems with examples provided apart from short information on swarm optimizations. The problem of swarms’ control described and possible solutions for it such as algorithm replacement, parameters change, control through environment and leaders. Apart from that fields for possible future research noted.

Swarm Intelligence Based Reputation Model for Open Multi agent Systems

2010 ◽  
pp. 248-266 ◽  
Author(s):  
Saba Mahmood ◽  
Azzam ul Asar ◽  
Hiroki Suguri ◽  
Hafiz Farooq Ahmad
Keyword(s):  
Swarm Intelligence ◽  
Multiagent Systems ◽  
Dynamic Environment ◽  
Sources Of Information ◽  
Multi Agent Systems ◽  
Interacting Agents ◽  
Utility Gain ◽  
Multi Agent ◽  
Trust Models ◽  
Reputation Model

In open multiagent systems, individual components act in an autonomous and uncertain manner, thus making it difficult for the participating agents to interact with one another in a reliable environment. Trust models have been devised that can create level of certainty for the interacting agents. However, trust requires reputation information that basically incorporates an agent’s former behaviour. There are two aspects of a reputation model i.e. reputation creation and its distribution. Dissemination of this reputation information in highly dynamic environment is an issue and needs attention for a better approach. We have proposed a swarm intelligence based mechanism whose self-organizing behaviour not only provides an efficient way of reputation distribution but also involves various sources of information to compute the reputation value of the participating agents. We have evaluated our system with the help of a simulation showing utility gain of agents utilizing swarm based reputation system. We have utilized an ant net simulator to compute results for the reputation model. The ant simulator is written in c

scholarly journals A Multi-Agent Mah Jong Playing System: Towards Real-Time Recognition of Graphic Units in Graphic Representations

10.14311/416 ◽  
2003 ◽  
Vol 43 (2) ◽  
Author(s):  
H. Achten ◽  
J. Jessurun
Keyword(s):  
Architectural Design ◽  
Building Blocks ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Search Activity ◽  
Agent System ◽  
Agent Systems ◽  
Graphic Representations ◽  
Multi Agent ◽  
Important Means

In architectural design, sketching is an important means to explore the first conceptual developments in the design process. It is necessary to understand the conventions of depiction and encoding in sketches and drawings if we want to support the architect in the sketching activity. The theory of graphic units provides a comprehensive list of conventions of depiction and encoding that are widely used among architects. These graphic units form useful building blocks to understand design drawings. We investigate whether it is possible to build a system that can recognize graphic units. The technology we are looking at is multi-agent systems. It was chosen for the following reasons: agents can specialize in graphic units, a multi-agent system can deal with ambiguity through negotiation and conflict resolution, and multi-agent systems function in dynamically changing environments. Currently there is no general approach or technology available for multi-agent systems. Therefore, in our research we first set out to make such a multi-agent system. In order to keep the complexity low, we first aim to make a system that can do something simple: playing Mah Jong solitary. The Mah Jong solitary system shares the following important features with a multi-agent system that can recognize graphic units: (1) specialized agents for moves; (2) negotiation between agents to establish the best move; (3) a dynamically changing environment; and (4) search activity for more advanced strategies. The paper presents the theoretical basis of graphic units and multi-agents systems, followed by a description of the multi-agent framework and its implementation. A number of systems that can play Mah Jong at various degrees of competence and accordingly degrees of complexity of multi-agent system, are distinguished. Finally, the paper demonstrates how the findings are informative for a system that can recognize graphic units.

Web Services Integration in Multi-Agent Systems

2010 ◽  
pp. 1-17
Author(s):  
Davide Guidi ◽  
Mauro Gaspari ◽  
Giuseppe Profiti
Keyword(s):  
Web Services ◽  
Autonomous Agents ◽  
Building Blocks ◽  
Multi Agent Systems ◽  
Fully Integrated ◽  
Agent Systems ◽  
Services Integration ◽  
Service Oriented ◽  
Multi Agent ◽  
Web Infrastructure

The development of distributed systems is influenced by several paradigms. For example, in the last few years, great emphasis has been placed on Service Orientation. In addition, technologies such as Web services are now considered standard, deployed in common development tools and widely used. However, despite this recent trend, the constantly growing number of powerful personal devices will inevitably revitalize the interest in another paradigm known as Autonomous Agents. Agents are in fact considered one of the main building blocks of the emerging next generation Web infrastructure. Web services are very important resources for agents. Agents should be able to retrieve, execute and compose Web services, providing an intelligent and personalized support to users. On the other hand, agents should also be able to export their functionalities as Web services in order to be fully integrated in the Service Oriented paradigm. In this chapter we present a survey of the current state of the art about Web services integration in open Multi-Agent Systems (MAS). Considering these approaches, we identify a set of requirements needed to achieve full integration and we present a communication infrastructure, which satisfies these requirements.

scholarly journals Behavior Selection Metaheuristic Search Algorithm for the Pollination Optimization: A Simulation Case of Cocoa Flowers

Algorithms ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 230
Author(s):  
Willa Ariela Syafruddin ◽  
Rio Mukhtarom Paweroi ◽  
Mario Köppen
Keyword(s):  
Optimization Problems ◽  
Search Algorithm ◽  
Random Search ◽  
Optimization Methods ◽  
Multi Agent Systems ◽  
Real World Problem ◽  
Multi Agent ◽  
Flower Type ◽  
Excellent Source

Since nature is an excellent source of inspiration for optimization methods, many optimization algorithms have been proposed, are inspired by nature, and are modified to solve various optimization problems. This paper uses metaheuristics in a new field inspired by nature; more precisely, we use pollination optimization in cocoa plants. The cocoa plant was chosen as the object since its flower type differs from other kinds of flowers, for example, by using cross-pollination. This complex relationship between plants and pollinators also renders pollination a real-world problem for chocolate production. Therefore, this study first identified the underlying optimization problem as a deferred fitness problem, where the quality of a potential solution cannot be immediately determined. Then, the study investigates how metaheuristic algorithms derived from three well-known techniques perform when applied to the flower pollination problem. The three techniques examined here are Swarm Intelligence Algorithms, Individual Random Search, and Multi-Agent Systems search. We then compare the behavior of these various search methods based on the results of pollination simulations. The criteria are the number of pollinated flowers for the trees and the amount and fairness of nectar pickup for the pollinator. Our results show that Multi-Agent System performs notably better than other methods. The result of this study are insights into the co-evolution of behaviors for the collaborative pollination task. We also foresee that this investigation can also help farmers increase chocolate production by developing methods to attract and promote pollinators.

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