scholarly journals A multi-agent environment in robotics

Robotica ◽  
1991 ◽  
Vol 9 (4) ◽  
pp. 431-440 ◽  
Author(s):  
Eugénio Oliveira ◽  
R. Camacho ◽  
C. Ramos
Keyword(s):  
Intelligent System ◽  
Multi Agent Systems ◽  
World Model ◽  
Agent Systems ◽  
Distributed Ai ◽  
Input Queue ◽  
Cooperative Agents ◽  
Software Modules ◽  
Multi Agent ◽  
Self Knowledge

SUMMARYThe use of Multi-Agent Systems as a Distributed AI paradigm for Robotics is the principal aim of our present work. In this paper we consider the needed concepts and a suitable architecture for a set of Agents in order to make it possible for them to cooperate in solving non-trivial tasks.Agents are sets of different software modules, each one implementing a function required for cooperation. A Monitor, an Acquaintance and Self-knowledge Modules, an Agenda and an Input queue, on the top of each Intelligent System, are fundamental modules that guarantee the process of cooperation, while the overall aim is devoted to the community of cooperative Agents. These Agents, which our testbed concerns, include Vision, Planner, World Model and the Robot itself.

Role-Based Multi-Agent Systems

2011 ◽  
pp. 254-285 ◽  
Author(s):  
Haibin Zhu ◽  
MengChu Zhou
Keyword(s):  
System Design ◽  
Multi Agent Systems ◽  
Agent System ◽  
Agent Systems ◽  
Collaborative Behavior ◽  
Cooperative Agents ◽  
Multi Agent ◽  
Role Based ◽  
Information Personalization

Agent system design is a complex task challenging designers to simulate intelligent collaborative behavior. Roles can reduce the complexity of agent system design by categorizing the roles played by agents. The role concepts can also be used in agent systems to describe the collaboration among cooperative agents. In this chapter, we introduce roles as a means to support interaction and collaboration among agents in multi-agent systems. We review the application of roles in current agent systems at first, then describe the fundamental principles of role-based collaboration and propose the basic methodologies of how to apply roles into agent systems (i.e., the revised E-CARGO model). After that, we demonstrate a case study: a soccer robot team designed with role specifications. Finally, we present the potentiality to apply roles into information personalization.

Intelligent Traceability System of Containerized Goods

2013 ◽  
Vol 309 ◽  
pp. 241-251 ◽  
Author(s):  
Mourad Abed ◽  
Imen Charfeddine ◽  
Mounir Benaissa ◽  
Marta Starostka-Patyk
Keyword(s):  
Supply Chain ◽  
Intelligent System ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Traceability System ◽  
Transport Chain ◽  
Multimodal Transport ◽  
Literature Reviews ◽  
Different Types ◽  
Multi Agent

In recent year, many countries across in the world have made traceability a compulsory procedure in the Supply Chain. The Supply Chain is distributed collaborative environments involves the acquisition and use of extensive informational and physical flows. The flows management seems a complex task for the actors of the multimodal transport chain which the transport is the major driver in a Supply Chain. The literature reviews throws light on the traceability in the Supply Chain Management (SCM) shows the lack of interoperability and flexibility in data management systems hinders the work of traceability. And it introduces the importance and complexity of multimodal transport operations. To ensure effective traceability all along this chain, we relied on the agent paradigm and the ontology which facilitate the integration of goods data in order to exploit and reuse. Indeed, to ensure communication and interoperability of these data we relied on Multi-Agent Systems, due to their characteristics of autonomy, sociability and responsiveness that are generally associated. The Multi-Agent Systems can build flexible systems whose behaviors are complex and complicated due to the combination of different types of agents. With a focus on the importance of the concept of the traceability, the objective of this work is to propose an intelligent system for the traceability of containerized goods in the context of multimodal transport: Intelligent Traceability System of Containerized Goods (i-TSCG).

Event-triggered flocking control of multi-agent systems in presence of cyber attacks

2021 ◽  
pp. 095441002098637
Author(s):  
Neda Amirian ◽  
Saeed Shamaghdari
Keyword(s):  
Hybrid Control ◽  
Cyber Attacks ◽  
Multi Agent Systems ◽  
Consensus Protocol ◽  
Agent Systems ◽  
Cooperative Agents ◽  
Event Triggering ◽  
Multi Agent ◽  
Update Rules ◽  
Event Triggered

We propose an event-triggered control system for multi-agent systems with the double-integrator network to achieve resilient flocking behavior in the presence of cyberattacks. The method can manage connectivity and increase the robustness of the topology graph via a three-state hybrid control. Each state of hybrid control has a distinct triggering condition. The developed event-triggered update rules can mitigate the influence of the noncooperative agents using the weighted mean subsequence reduced algorithm and reduce unnecessary communication among them. As a result, the performance of the system can effectively improve. Convergence of the velocity and orientation of the agents is guaranteed by using this type of control structure and resilient consensus protocol. We assume that the bound on the number of noncooperative agents in the neighbor sets of cooperative agents is known. The proposed scheme with the event-triggering rules can avoid Zeno behaviors inherently. Finally, a simulation example is worked out to demonstrate the effectiveness of the proposed approach.

scholarly journals Multi-Agent System Overview: Architectural Designing using Practical Approach

2013 ◽  
Vol 5 (2) ◽  
pp. 85-93 ◽  
Author(s):  
Mohamed Osama Khozium
Keyword(s):  
Board Of Directors ◽  
Intelligent System ◽  
Online Communication ◽  
Board Members ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Agent Systems ◽  
Multi Agent ◽  
Real Challenge

A software agent should be autonomous, flexible, robust and social. The increasing importance of the Multi-Agent System (MAS) has led to the greater availability of tools designed to facilitate their creation and use. To devise agents is considered a real challenge which faces analysts and designers during development of any multi-agent systems. This paper proposes a methodology to determine, clarify and differentiate among agents during development of multi-agent systems using goals and functionalities grouping approach. A step by step case of study is presented to explain the proposed methodology for the creation of an Online Intelligent System (OIS) for Board of Directors guide using Multi-Agent System to facilitate online communication between the board members and their president to monitor the policies and productivity of the company.

AN INFRASTRUCTURE FOR ENGINEERING COOPERATIVE AGENTS

2000 ◽  
Vol 10 (06) ◽  
pp. 681-711 ◽  
Author(s):  
SOE-TSYR YUAN ◽  
ZENG-LUNG WU
Keyword(s):  
Success Factors ◽  
Critical Mass ◽  
Success Factor ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Bottom Up ◽  
Agent Systems ◽  
Cooperative Agents ◽  
Multi Agent

Currently, systems of cooperative agents (multi-agent systems), possessing the capabilities of autonomy, adaptation, and cooperation, are being used in an increasingly wide variety of application areas, and the conversation-based multi-agent system design is the major design for those multi-agent systems. Supposedly, conversation-based multi-agent systems should have been prevailing enough for tackling dynamic aspects of problems in a variety of domains. However, for industries, multi-agent systems are still found to be in the birth stage where they only show their new values in anticipation for further explorations and improvements in order to attract critical mass of users of information executives or software developers. Nevertheless, what are the success factors that can result in a critical mass of multi-agent system designers? This paper shows one possible success factor — an infrastructure for the bottom-up design of multi-agent systems. The bottom-up design makes it possible for agents to be reassembled into multi-agent systems and reused as needed. However, what do we need to successfully support the bottom-up design? This paper is the first attempt to present a tool that fully supports the bottom-up design of multi-agent systems. The tool has three parts. The first part is a wrapper that wraps each agent so that it exempts the designers from the careful detailed deployment of the inter-relationships between cooperation knowledge and task knowledge inside the agent. This wrapper should be independent of the functions of agents. The second part is an environment that can support the wrapper to automate the cooperation process on behalf of agents. The third part is a graphical assembly panel for developers to visually configure wrapped agents residing at different places of the Internet into a working multi-agent system.

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