Contract Net Model Research Articles

Computer Simulation and Simulation of Mechanical and Electrical Equipment based on Artificial Intelligence Algorithms

The computer in mechanical and electrical equipment can now detect equipment faults through simulation thanks to the advancement of artificial intelligence (AI) technology, which makes it convenient to monitor mechanical and electrical equipment. This paper begins with a quick introduction to Agent and the Agent system, explains how Agent is applied in the current context, then analyzes the hierarchical fault diagnostic model, identifies its flaws, and suggests improvement techniques. To increase the model’s accuracy and speed of operation, the contract net model and D-S (Dempster-Shafer) evidence theory are then incorporated. Finally, simulation experiments are used to confirm the accuracy and consistency of this model. According to the experimental findings, this optimization model runs at a pace that is noticeably faster than that of other models when subjected to the same workload, demonstrating the model’s efficacy. Models 1, 2, and 3 are put side by side to demonstrate how clearly multi-task processing may cut down on the model’s running time. In the second experiment, samples of mechanical and electrical equipment defect data are taken from two groups. The results of the comparative experiments demonstrate that the optimized model in this work can be reliable up to a maximum of 0.91 and a minimum of 0.63. It is demonstrated that the model in this work is rational by the fact that among the four types of fault prediction, the optimized model’s reliability is significantly greater than the traditional model’s. The research described in this publication therefore has some reference value for computer simulation of electromechanical equipment.

A contract-net model for foraging agents in dynamic environment

A contract-net model for foraging agents in dynamic environment

Platform-level Distributed Warfare Model-based on Multi-Agent System Framework

The multi-agent paradigm has become a useful tool in solving military problems. However, one of key challenges in multi-agent model for distributed warfare could be how to describe the microcosmic tactical warfare platforms actions. In this paper, a platform-level distributed warfare model based on multi-agent system framework is designed to tackle this challenge. The basic ideas include: Establishing multi-agent model by mapping from tactical warfare system’s members, i.e., warfare platforms, to respective agents; performing task decomposition and task allocation by using task-tree decomposition method and improved contract net protocol model technique; and implementing simulation by presenting battlefield terrain environment analysis algorithm based on grid approach. The simulation demonstration results show that our model provides a feasible and effective approach to supporting the abstraction and representation of microcosmic tactical actions for complex warfare system. Defence Science Journal, 2012, 62(1), pp.180-186 , DOI:http://dx.doi.org/10.14429/dsj.62.964

Ant Colony Intelligence in Flexible Manufacturing Scheduling Using Contract-Net Model

This paper builds an efficient agent-based flexible scheduling for real-world manufacturing systems. Considering the alternative processes and alternative machines, the allocation of manufacturing resources is achieved through negotiation among the job and machine agents in a multi-agent system (MAS). Ant Colony Intelligence (ACI) is proposed to be combined with Contract Net Protocol (CNP) so as to make agents adaptive to changing circumstances. ACI is integrated into both machine agents and job agents to solve the task allocation and sequencing problem. CNP is introduced to allow the agents to cooperate and coordinate their local schedules in order to find globally near-optimal robust schedules. The negotiation protocol is an interactive bidding mechanism based on the hybrid contract net protocol. The implementation of the issues using CNP model is discussed. Experimental results verify the effectiveness and efficiency of the proposed algorithm integrated with ant-inspired coordination.

Multi-Agent Systems for Adaptive and Efficient Job Scheduling Service in Grids

In this paper we propose an adaptive efficient job scheduling service model on Grids using multi agent systems and a market like Service level Agreement (SLA) negotiation protocol based on the Contract Net model. This job scheduling service model involves four types of agents: service user agents, service provider agents, local scheduler agents and inter-grid agents. Service provider agents provide services to service user agents by allocating resources using local scheduler agents. Service provider agents provide services to service user agents by allocating resources using local scheduler agents. The service provider agents may contact the inter-grid agents if enough resources are not available in their own grid. Inter-grid agents provide resources from the neighboring grid. The service provider agent may adapt the dedicated service according to its interactions with service user agent. The SLA negotiation protocol is a hierarchical bidding mechanism involving negotiations between the four agents. In this protocol, the agents exchange SLA announcements, SLA-bid, and SLA-awards to negotiate the schedule of jobs on Grid Compute resources. To deal with the presence of uncertainties, re-negotiation is used to allow the agents to re-negotiate the SLA in failure. The full text of the article is not available in the cache. Kindly refer the IJCA digital library at www.ijcaonline.org for the complete article. In case, you face problems while downloading the full-text, please send a mail to editor at editor@ijcaonline.org

A survey of bargaining models for grid resource allocation

Whereas it is noted that various types of auctions, commodity market models, and contract-net (tendering) model are more widely used for managing Grid resources, this paper focuses on discussing bargaining (negotiation) models for Grid resource management. To this end, this survey supplements and complements existing surveys by reviewing, comparing, and highlighting the very few extant research initiatives on applying bargaining as a mechanism for managing Grid resources. The contributions of this paper are (i) discussing the motivations for considering bargaining models for Grid resource management, (ii) discussing the issues in building bargaining mechanisms for Grid resource management, (iii) comparing the strategies and protocols of state-of-the-art bargaining models for Grid resources, and (iv) discussing possible new directions.

A proposal for decentralized cooperative decision-making in chemical batch operation

The objects of this study are to discuss an intelligent solution of dynamic unit-assignment problems in the decentralized cooperative operation for a new type of chemical batch plant, i.e. a pipeless batch plant, and to propose a decentralized cooperative method of multiple-criteria decision-making in process planning. For these purposes, two techniques of Distributed Artificial Intelligence (DAI) and the Analytic Hierarchy Process (AHP) are applied. Negotiation is realized by using message passing based on the contract net model, and a method of decentralized dynamic unit-assignment makes local scheduling possible. By integrating such multiple local schedules, cooperative operation and management of the whole plant may be achieved. The AHP is applied to the decision-making in selecting a suitable unit among alternative ones. Multiple functional units, such as process managers, reactors and stations, make game-like decisions based on multiple criteria of static evaluation and dynamic evaluation. Such a system is proposed to realize the flexibility and adaptability required for future chemical batch plants, rather than optimality.