This 2002 book investigates the opportunities in building intelligent decision support systems offered by multi-agent distributed probabilistic reasoning. Probabilistic reasoning with graphical models, also known as B...
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ISBN:
(数字)9780511148125
ISBN:
(纸本)9780521813082
This 2002 book investigates the opportunities in building intelligent decision support systems offered by multi-agent distributed probabilistic reasoning. Probabilistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become increasingly an active field of research and practice in artificialintelligence, operations research and statistics. The success of this technique in modeling intelligent decision support systems under the centralized and single-agent paradigm has been striking. Yang Xiang extends graphical dependence models to the distributed and multi-agent paradigm. He identifies the major technical challenges involved in such an endeavor and presents the results. The framework developed in the book allows distributed representation of uncertain knowledge on a large and complex environment embedded in multiple cooperative agents, and effective, exact and distributed probabilistic inference.
This paper presents a new soliton approach to hyper-distributed hyper-parallel self-organizing dynamic scheduling for task allocations among rational autonomous agents in a multi-agent system (MAS). This approach can ...
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This paper presents a new soliton approach to hyper-distributed hyper-parallel self-organizing dynamic scheduling for task allocations among rational autonomous agents in a multi-agent system (MAS). This approach can overcome many drawbacks of other mechanisms currently used for coalition formation and cooperation in MAS. The thorny problems, such as overabundant bid, social behaviors, colony intelligence, variable neighbors, and interdepen-dency, can easily be treated by using the proposed approach, whereas they are very difficult for other conventional approaches. The simulation on a distributed transport scheduling sys-tem shows the soliton approach featured by hyper-parallelism, effectiveness, openness, dynamic alignment and adaption.
The secondary voltage control of power systems initiated by EDF has been developed successfully and applied mainly for the generator AVRS to improve power-system voltage stability. Work on secondary voltage control is...
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The secondary voltage control of power systems initiated by EDF has been developed successfully and applied mainly for the generator AVRS to improve power-system voltage stability. Work on secondary voltage control is presented involving various types of power-system voltage controllers, AVRs, SVCs and STATCOMs, for a new application: power-system voltage management in system contingencies. The secondary voltage control is proposed, to be implemented based on the principles of multi-agent system theory, an active branch of applications in the distributed artificial intelligence. An example power system is presented to demonstrate the necessity of the secondary voltage control among an AVR, an SVC and a STATCOM installed in the power system, and also to illustrate the success of applying the multi-agent co-ordination for their secondary voltage control in system contingencies.
The paper describes an experimental multi-agent system developed for and aimed at a computer-supported project-oriented production planning. The system is based on a heterogeneous hierarchy of agents of three types th...
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The paper describes an experimental multi-agent system developed for and aimed at a computer-supported project-oriented production planning. The system is based on a heterogeneous hierarchy of agents of three types that reflect the managerial structure of the manufacturing enterprise. To improve the system efficiency, a new formalism-called tri-base model-of the multi-agent internal communication/negotiation mechanism has been introduced. The tri-base model that has been tested in an industrial environment is treated in detail in the paper. (C) 2001 Elsevier Science Ltd. All rights reserved.
Automated Guided Vehicle (AGV) systems are complex to design and to implement. Inefficiencies become difficult to avoid or even to control. This paper presents the theory behind a novel agent based AGV controller that...
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Automated Guided Vehicle (AGV) systems are complex to design and to implement. Inefficiencies become difficult to avoid or even to control. This paper presents the theory behind a novel agent based AGV controller that aims to control the flow of AGVs in an effective manner and, therefore, overcome the inefficiencies that can be found in complex designs. Agents are simple entities that interact with other agents to produce an emergent behaviour that is not explicitly programmed into them. The AGV controller presented uses agents as traffic managers to allow access to points and segments in the guide path. Each agent has a rule base that it uses to assess the enquiries that it receives from an AGV. Each enquiry is evaluated only at the smallest possible part of the guide path rather than the entire guide path. AGVs are then able to allocate segments and points on their paths depending on the result of each enquiry. Simulation experiments were used to test the cont roller and an overview is presented.
Traditional Enterprise Resource Planning (ERP) systems strongly focus on planning internal production and logistics disregarding external effects on upstream and downstream contractors in the value chain. Supply Chain...
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Traditional Enterprise Resource Planning (ERP) systems strongly focus on planning internal production and logistics disregarding external effects on upstream and downstream contractors in the value chain. Supply Chain Management accounts for these effects: but, on the other hand, often fails due to the complexity of global planning of the entire supply network. Our paper presents existing approaches using so called Multi Agent Systems, keeping the natural decentralized structure of the problem and locusing on the interaction protocols of the software agents. We present a framework for the integration of these concepts in an open Multi Agent Architecture and discuss dispositive negotiation protocols based on the propagation of time-dependent supply and demand functions.
The cooperation of multi-robot that is based on the Multi-Agent System (MAS) theory of distributed artificial intelligence has become a hotspot in the robotics R&D. In the research, the communication and cooperati...
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ISBN:
(纸本)0780371909
The cooperation of multi-robot that is based on the Multi-Agent System (MAS) theory of distributed artificial intelligence has become a hotspot in the robotics R&D. In the research, the communication and cooperation of multi-agent become the key problem for gaining the dynamic running information of cooperating robots. In this paper we introduce the communication modes for agent and provide a common strategy (which aims at the communication resources of multi-agent model) - the CSMA/CD (Carrier Sense Multiple Access with Collision Detection) protocol which is based on the transmittal medium. It supports the cable-communication of multi-robot and the experiments prove its validity.
COMPUTERS PROVIDE FRESH OPPORTUNITIES for enhancing and understanding collaborative learning. They permit new research methodologies such as simulations of cooperating agents, and they present new design challenges in...
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Traditional methods for creating intelligent computational systems have privileged private "internal" cognitive and computational processes. In contrast, Swarm intelligence argues that human intelligence der...
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ISBN:
(数字)9780080518268
ISBN:
(纸本)9781558605954
Traditional methods for creating intelligent computational systems have privileged private "internal" cognitive and computational processes. In contrast, Swarm intelligence argues that human intelligence derives from the interactions of individuals in a social world and further, that this model of intelligence can be effectively applied to artificially intelligent systems. The authors first present the foundations of this new approach through an extensive review of the critical literature in social psychology, cognitive science, and evolutionary computation. They then show in detail how these theories and models apply to a new computational intelligence methodology—particle swarms—which focuses on adaptation as the key behavior of intelligent systems. Drilling down still further, the authors describe the practical benefits of applying particle swarm optimization to a range of engineering problems. Developed by the authors, this algorithm is an extension of cellular automata and provides a powerful optimization, learning, and problem solving method. This important book presents valuable new insights by exploring the boundaries shared by cognitive science, social psychology, artificial life, artificialintelligence, and evolutionary computation and by applying these insights to the solving of difficult engineering problems. Researchers and graduate students in any of these disciplines will find the material intriguing, provocative, and revealing as will the curious and savvy computing professional.
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