Negotiation as a metaphor for distributed problem solving
Distributed Artificial Intelligence
Artificial Intelligence
The CIMOSA business modelling process
Computers in Industry - Special issue: validation of CIMOSA
Market-oriented programming: some early lessons
Market-based control
Case studies in object oriented analysis & design
Case studies in object oriented analysis & design
An overview of distributed artificial intelligence
Foundations of distributed artificial intelligence
Agent-based modeling and management of manufacturing systems
Computers in Industry - Special issue: ASI '95
The Unified Modeling Language user guide
The Unified Modeling Language user guide
A methodology for agent-oriented analysis and design
Proceedings of the third annual conference on Autonomous Agents
Decentralised resource allocation planning through negotiation
BASYS '98 Proceedings of the 3rd IEEE/IFIP international conference on Intelligent systems for manufacturing : multi-agent systems and virtual organizations: multi-agent systems and virtual organizations
Manufacturing Systems Modelling, Specification and Analysis
Proceedings of the IFIP WG5.7 Working Conference on Evaluation of Production Management Methods
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This paper presents a multi-agent conceptual model for resource allocation in a manufacturing environment. To attain this purpose a framework called M-DRAP - Multi-agent Dynamic Resources Allocation Planning - was developed. Multi-agent systems have been employed as a solution for problems that require decentralization and distribution in both decision-making and execution process. This is a premise in many information systems where (i) the domain involves intrinsic distribution of data, problem-solving capabilities and responsibilities; (ii) it is necessary to maintain the autonomy of the subparts, without lost of organizational structure; and (iii) the problem solution cannot be completely described a priori due to the possibility of real-time perturbations in the environment (equipment failures, for example) and also as a consequence of the natural dynamics of the business process. The main contribution of this work is the proposition of a set of activities and models defining a framework to represent multi-agent systems for business process under an enterprise model perspective.