Agent-Based Micro Machining System With Cusp-Height-Minimized Tool Sequence

2009 ◽  
Author(s):  
Kyung-Hoon Wie ◽  
Hyung-Jung Kim ◽  
Young-Sun Hong ◽  
Sung-Hoon Ahn
Keyword(s):  
Cost Estimation ◽  
Manufacturing Systems ◽  
Micro Machining ◽  
Multi Agent System ◽  
Agent System ◽  
Agent Based ◽  
Development Framework ◽  
Macro Scale ◽  
Machining System ◽  
Multi Agent

Agent technology can provide a systematic way to design and implement efficiently distributed intelligent manufacturing systems. Multi-agent system has been recognized as a promising paradigm to integrate a number of agents with different functions. In micro machining field many researchers have been studied the machining characteristics since the influence of underlying mechanisms are fundamentally different from macro-scale machining. This paper presents an agent-based micro machining system. To cover the process planning step for micro machining, basic agents such as cutting tool selection, tool-path generation, and machining cost estimation were implemented. To build and integrate these distributed agents, Java Agent Development Framework (JADE) was used. Throughout this system the selection of optimal roughing tool for semi-finishing stage was implemented by providing automated process planner for micro machining to the engineers. Machining data bases were constructed to store the information of materials, tools, and capability of available machine tools. A designed part can be uploaded to the Micro Machining (MM) agent as a Stereo Lithography (STL) format. MM agent can provide process parameters for 3-axis micro milling and tool sequence for cost-optimal machining automatically. Machining Cost Estimation agent can calculate micro machining cost for the designed part. To test the multi-agent system, a surface of micro-surface feature was fabricated with micro end-mills.

scholarly journals A multi-agent-based approach for address geocoding in poorly mapped areas through public company data

2021 ◽  
Vol 3 (1) ◽  
pp. 1-9
Author(s):  
Mouhamad Al Mansour KEBE ◽  
Roger Marcelin FAYE ◽  
Claude LISHOU
Keyword(s):  
Current Knowledge ◽  
Original Method ◽  
Local Context ◽  
Multi Agent System ◽  
Industrialized Countries ◽  
Agent System ◽  
Agent Based ◽  
Public Company ◽  
Spatial Coordinates ◽  
Multi Agent

In this study, we present an original method that enhances geocoding systems in poorly mapped areas thanks to public company data and a multi-agent system. In contrast with industrialized countries, many developing countries lack formal postal address systems assignments and usage, making the operation of translating text-based addresses to absolute spatial coordinates, known as geocoding, a big challenge. We recreated a standard of address as it is perceived and used by local people, a kind of non-official national address standard since there is no official one in these areas. Then, we designed a multi-agent system in which agents are assigned different tasks of geocoding process and can perform negotiation to achieve a global objective: find the best possible match or approximation of a location-based on current knowledge. Verification of the usefulness of the proposed approach is made in comparison with Google Geocoding API which shows that the proposed approach has great potential to geocode addresses considering local context semantic issues.

Evolutionary Computation as a Paradigm for Engineering Emergent Behaviour in Multi-Agent Systems

2011 ◽  
pp. 118-136 ◽  
Author(s):  
Robert E. Smith ◽  
Claudio Bonacina
Keyword(s):  
Evolutionary Computation ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Future Directions ◽  
Agent Based ◽  
Agent Systems ◽  
Emergent Behaviour ◽  
Shaping System ◽  
Multi Agent

In the multi-agent system (MAS) context, the theories and practices of evolutionary computation (EC) have new implications, particularly with regard to engineering and shaping system behaviors. Thus, it is important that we consider the embodiment of EC in “real” agents, that is, agents that involve the real restrictions of time and space within MASs. In this chapter, we address these issues in three ways. First, we relate the foundations of EC theory to MAS and consider how general interactions among agents fit within this theory. Second, we introduce a platform independent agent system to assure that our EC methods work within the generic, but realistic, constraints of agents. Finally, we introduce an agent-based system of EC objects. Concluding sections discuss implications and future directions.

Agent-Based Infrastructure for Dynamic Composition of Grid Services

2010 ◽  
pp. 911-936
Author(s):  
Matthew Adigun ◽  
Johnson Iyilade ◽  
Klaas Kabini
Keyword(s):  
Service Composition ◽  
Research Effort ◽  
Multi Agent System ◽  
Grid Services ◽  
Agent System ◽  
Agent Based ◽  
Dynamic Composition ◽  
Emerging Trends ◽  
Dynamic Service Composition ◽  
Multi Agent

The service-oriented computing paradigm is based on the assumption that existing services can be put together in order to obtain new composite services. This chapter focuses on how peer-to-peer architectures based on multi-agent systems can be used to build highly dynamic and reconfigurable infrastructure that support dynamic composition of grid services. The chapter starts by providing an overview of key technologies for SOC. It then introduces dynamic service composition and challenges of composing grid services. The authors further motivate for Multi-agent system approach in SOC and why it becomes important in service composition. They then present our research effort, AIDSEC, an agent-based infrastructure for dynamic service composition, describing its architecture, implementation and comparison with some related work in the literature. In addition, the chapter raises some emerging trends in SOC and the particular challenges they pose to service composition. They conclude by suggesting that a solution based on multi-agent system is required for composing services that possess capabilities of autonomy, reliability, flexibility, and robustness.

scholarly journals Routing Based Multi-Agent System for Network Reliability in the Smart Microgrid

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2992
Author(s):  
Niharika Singh ◽  
Irraivan Elamvazuthi ◽  
Perumal Nallagownden ◽  
Gobbi Ramasamy ◽  
Ajay Jangra
Keyword(s):  
Large Scale ◽  
Network Performance ◽  
Performance Metrics ◽  
Network Reliability ◽  
Operating Conditions ◽  
Multi Agent System ◽  
Agent System ◽  
Agent Based ◽  
Multi Agent ◽  
System Operating

Microgrids help to achieve power balance and energy allocation optimality for the defined load networks. One of the major challenges associated with microgrids is the design and implementation of a suitable communication-control architecture that can coordinate actions with system operating conditions. In this paper, the focus is to enhance the intelligence of microgrid networks using a multi-agent system while validation is carried out using network performance metrics i.e., delay, throughput, jitter, and queuing. Network performance is analyzed for the small, medium and large scale microgrid using Institute of Electrical and Electronics Engineers (IEEE) test systems. In this paper, multi-agent-based Bellman routing (MABR) is proposed where the Bellman–Ford algorithm serves the system operating conditions to command the actions of multiple agents installed over the overlay microgrid network. The proposed agent-based routing focuses on calculating the shortest path to a given destination to improve network quality and communication reliability. The algorithm is defined for the distributed nature of the microgrid for an ideal communication network and for two cases of fault injected to the network. From this model, up to 35%–43.3% improvement was achieved in the network delay performance based on the Constant Bit Rate (CBR) traffic model for microgrids.

A DAI-Based Framework for the Virtual Prototyping of Fluid Power Systems

Manufacturing ◽  
2002 ◽  
Author(s):  
S. C. Fok ◽  
G. L. Thimm ◽  
W. Xiang
Keyword(s):  
Power Systems ◽  
Virtual Prototyping ◽  
Control Agent ◽  
Distributed Artificial Intelligence ◽  
Fluid Power ◽  
Multi Agent System ◽  
Agent System ◽  
Agent Based ◽  
Multi Agent ◽  
Fluid Power Systems

This paper proposes a distributed artificial intelligence framework to address the co-ordination of interactions among the different standard virtual components during the virtual prototyping of fluid power systems. The approach considers the hydraulic system as a multi-agent system and associates each virtual hydraulic component to a domain agent. A control agent is used to co-ordinate the interactions in the multi-agent system. The representation of the proposed domain agents and the co-ordinated communication via the control agent are discussed in this paper. The paper also presents some details on the implementation of the proposed agent-based architecture and explains how agent communication and collaboration has been accomplished using Java and VRML.

scholarly journals PACA-ITS: A Multi-Agent System for Intelligent Virtual Laboratory Courses

2019 ◽  
Vol 9 (23) ◽  
pp. 5084
Author(s):  
Saima Munawar ◽  
Saba Khalil Toor ◽  
Muhammad Aslam ◽  
Esma Aimeur
Keyword(s):  
Practical Knowledge ◽  
Unified Modeling Language ◽  
Cognitive Model ◽  
Learning System ◽  
Virtual Laboratory ◽  
Multi Agent System ◽  
Agent System ◽  
Laboratory Courses ◽  
Development Framework ◽  
Multi Agent

This paper describes an intensive design leading to the implementation of an intelligent lab companion (ILC) agent for an intelligent virtual laboratory (IVL) platform. An IVL enables virtual labs (VL) to be used as online research laboratories, thereby facilitating and improving the analytical skills of students using agent technology. A multi-agent system enhances the capability of the learning system and solves students’ problems automatically. To ensure an exhaustive Agent Unified Modeling Language (AUML) design, identification of the agents’ types and responsibilities on well-organized AUML strategies is carried out. This work also traces the design challenge of IVL modeling and the ILC agent functionality of six basic agents: the practical coaching agent (PCA), practical dispatcher agent (PDA), practical interaction and coordination agent (PICA), practical expert agent (PEA), practical knowledge management agent (PKMA), and practical inspection agent (PIA). Furthermore, this modeling technique is compatible with ontology mapping based on an enabling technology using the Java Agent Development Framework (JADE), Cognitive Tutor Authoring Tools (CTAT), and Protégé platform integration. The potential Java Expert System Shell (Jess) programming implements the cognitive model algorithm criteria that are applied to measure progress through the CTAT for C++ programming concept task on IVL and successfully deployed on the TutorShop web server for evaluation. The results are estimated through the learning curve to assess the preceding knowledge, error rate, and performance profiler to engage cognitive Jess agent efficiency as well as practicable and active decisions to improve student learning.

Evolutionary Computation as a Paradigm for Engineering Emergent Behaviour in Multi-Agent Systems

2011 ◽  
pp. 2338-2350
Author(s):  
Robert E. Smith ◽  
Claudia Bonacina
Keyword(s):  
Evolutionary Computation ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Future Directions ◽  
Agent Based ◽  
Agent Systems ◽  
Emergent Behaviour ◽  
Shaping System ◽  
Multi Agent

In the multi-agent system (MAS) context, the theories and practices of evolutionary computation (EC) have new implications, particularly with regard to engineering and shaping system behaviors. Thus, it is important that we consider the embodiment of EC in “real” agents, that is, agents that involve the real restrictions of time and space within MASs. In this chapter, we address these issues in three ways. First, we relate the foundations of EC theory to MAS and consider how general interactions among agents fit within this theory. Second, we introduce a platform independent agent system to assure that our EC methods work within the generic, but realistic, constraints of agents. Finally, we introduce an agent-based system of EC objects. Concluding sections discuss implications and future directions.

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