Knowledge partitioning and allocation is crucial to DAI problem solving approach, This paper proposes heuristic solutions for knowledge base partitioning and allocation, Knowledge partitioning can be done by clusterin...
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Knowledge partitioning and allocation is crucial to DAI problem solving approach, This paper proposes heuristic solutions for knowledge base partitioning and allocation, Knowledge partitioning can be done by clustering rules of related objects in the knowledge base. Earlier clustering approaches use rule as the basic object of grouping, leaving the complexity of the solutions in the order of number of rules in the knowledge base. Hence, in order to reduce the complexity of partitioning, action is taken as the object of grouping, This leaves the complexity of the algorithm as O(k(2)M) where k is the number of partitions an M is the number of actions. The allocation of partitions to agents is done by considering the cost of communication to (and from) a partition from (to) all the partitions that are already allocated before it is allocated to an agent, The worst case time complexity of the allocation is O(k(2)log k(2)).
Large-scale micro-aerial vehicle (MAV) swarms provide promising solutions for situational awareness in applications such as environmental monitoring, urban surveillance, search and rescue, and so on. However, these sc...
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Large-scale micro-aerial vehicle (MAV) swarms provide promising solutions for situational awareness in applications such as environmental monitoring, urban surveillance, search and rescue, and so on. However, these scenarios do not provide localization infrastructure and limit cost and size of on-board capabilities of individual nodes, which makes it challenging for nodes to autonomously navigate to suitable preassigned locations. In this article, we present H-DrunkWalk, a collaborative and adaptive technique for heterogeneous MAV swarm navigation in environments not formerly preconditioned for operation. Working with heterogeneous MAV swarm, the H-DrunkWalk achieves high accuracy through collaboration but still maintains a low cost of the entire swarm. The heterogeneous MAV swarm consists of two types of nodes: (1) basic MAVs with limited sensing, communication, computing capabilities and (2) advanced MAVs with premium sensing, communication, computing capabilities. The key focus behind this networked MAV swarm research is to (1) rely on collaboration to overcome limitations of individual nodes and efficiently achieve system-wide sensing objectives and (2) fully take advantage of advanced MAVs to help basic MAVs improve their performance. The evaluations based on real MAV testbed experiments and large-scale physical-feature-based simulations show that compared to the traditional non-collaborative and non-adaptive method (dead reckoning with map bias), our system achieves up to 6x reductions in location estimation errors, and as much as 3x improvements in navigation success rate under the given time and accuracy constraints. In addition, by comprehensively considering the environment, heterogeneous structure, and quality of location estimation, our H-DrunkWalk brings 2x performance improvement (on average) as that of a hardware upgrade.
In this paper we build on the distributed artificial intelligence (DAI) Framework, which makes use of Belief-Desire-Intention extended (BDIx) agents residing on Device-to-Device (D2D) Mobile Devices in order to establ...
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In this paper we build on the distributed artificial intelligence (DAI) Framework, which makes use of Belief-Desire-Intention extended (BDIx) agents residing on Device-to-Device (D2D) Mobile Devices in order to establish D2D communication in an efficient, distributed, autonomous and flexible way. To demonstrate the potentials of this framework, in this work we focus on D2D Transmission Mode Selection in 5G. Specifically, we build on our previous work and develop an enhanced version of DAIS, a specific plan executed by the BDIx agents, for selecting the D2D Transmission mode that the D2D Devices will operate, aiming to offer improved Spectral Efficiency (SE) and Power Consumption (PC). To set a benchmark and allow for a fairer comparison we also enhance the distributed Sum Rate (DSR), a distributed algorithmic approach that focuses on maximising the aggregated data rate of all the links established in the network, with similar functionality as DAIS. Furthermore, an extensive comparative evaluation of the enhanced DAIS and DSR with a number of unsupervised ML clustering approaches adapted for D2D Communication(i.e., GMEANS, Fuzzy ART, MEC, and DBSCAN) is provided. Specifically, for each approach the following have been collected and compared: QoE and QoS Fairness, SE and PC achieved, efficiency of clusters created, signalling overhead caused (i.e., volume of messages exchanged), time execution delay, D2D Effectiveness, D2D Stability and D2D Productivity. Based on the insight gained into the performance of the enhanced DAIS, DSR and the unsupervised ML techniques, we discuss performance gain trade-offs in terms of SE and PC versus signalling overhead and control delay in responding to changes.
The supply chain management becomes an important criterion for the organizations success. In previous works we proposed an approach, based on interactive autonomous entities, in order to moderate the Bullwhip Effect, ...
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The supply chain management becomes an important criterion for the organizations success. In previous works we proposed an approach, based on interactive autonomous entities, in order to moderate the Bullwhip Effect, which is an emerging phenomenon of the demand amplification within a distributed Supply Chain. A Multi-Agent architecture is then proposed to design this distributed chain through interactive software agents. In this paper, we focus on a higher perturbation mode so we propose to adopt a more advanced interaction form between the autonomous entities. The goal is to avoid, in a crisis situation, and thanks to a Cooperative Negotiation Protocol, the stockout condition by balancing the resources provisions throughout the system. Simulation results prove the pertinence of the proposed solution.
Over the past ten years a myriad of knowledge-based expert systems have been developed and deployed. These systems have a narrow scope and usually operate in stand-alone mode. They also follow different implementation...
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Over the past ten years a myriad of knowledge-based expert systems have been developed and deployed. These systems have a narrow scope and usually operate in stand-alone mode. They also follow different implementation philosophies and use a variety of reasoning methods. To address problems of wider scope, researchers have developed systems that utilize either centralized or distributed computational models. Each of these systems is homogeneous, and due to the way developed, prohibitively expensive for real-world settings. In this paper we present OMNI, a framework for integrating existing knowledge-based systems in a way that they can cooperate during problem-solving while they remain distributed over a computing environment.
This paper describes a general framework for conflict resolution being implemented on the HOLOS multi-agent scheduling system. The framework is integrated with the planning and execution supervision activities, emphas...
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This paper describes a general framework for conflict resolution being implemented on the HOLOS multi-agent scheduling system. The framework is integrated with the planning and execution supervision activities, emphasizing the importance of local supervision actions. Conflicts are classified in levels and types, and the specific actions for their resolution, carried out dming scheduling genemtion, after its generation and during its execution, are also presented. A significant part ofthe conflict resolution process is supported by using the user guide negotiation approach. Finally, the decentralized scheduling supervision process is shown.
While coupling locally dispersed producers and consumers to large distributed networks comes with different socio-economic advantages as increase in production, higher market adaptability and higher resource efficienc...
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While coupling locally dispersed producers and consumers to large distributed networks comes with different socio-economic advantages as increase in production, higher market adaptability and higher resource efficiency, an immanent disadvantage is the accompanying raise in control complexity. distributed agent-based control approaches are envisioned as a solution for managing distributed and complex production, supply, and infrastructure networks. Nevertheless they are difficult to be analyzed and hard to be handled. The major challenges coming with distributed control solutions may be found in the field of stability problems such as oscillatory network conditions potentially leading to network collapses. In this paper a general modeling and stability analysis approach for networked nodes is presented and applied on a marketplace of an agent-based smart grid system to distribute an energy demand between producers. Finally the analytical results are evaluated on a smart grid simulation.
The distributed coordination problem can be described as " how should the local scheduling of activities at each agent be affected by non-local concerns and constraints ?" Partial global planning (PGP) is a ...
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The distributed coordination problem can be described as " how should the local scheduling of activities at each agent be affected by non-local concerns and constraints ?" Partial global planning (PGP) is a flexible approach to distributed coordination that allows agents to respond dynamically to their current situation. It is based on detecting relationships in the computational goal structures of the distributed agents. However, the detailed PGP mechanisms depend on the existence and availability of certain characteristics and structures that are idiosyncratic to the distributed Vehicle Monitoring Testbed (DVMT). Generalized Partial Global Planning tries to extend the PGP approach by communicating more abstract and hierarchically organized information, detecting in a general way the coordination relationships that are needed by the partial global planning mechanisms, and separating the process of coordination from local scheduling. This new characterization of partial global planning has less communication overhead and can be more easily adapted and extended to new styles of problem solving and new multi-agent environments that have different characteristics from the original DVMT. This paper first describes the coordination problem as it was viewed by the PGP algorithm, and then extensions to that problem. It then briefly describes our model of task structures and coordination relationships. Finally, we show how the PGP algorithm, as an example, can be described using our method.
This paper presents a Nuclear Power Plant (NPP) distributed control system developped as part of a CEA (french atomic agency) research program. From the analysis of plant operation principles in french Pressurized Wat...
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This paper presents a Nuclear Power Plant (NPP) distributed control system developped as part of a CEA (french atomic agency) research program. From the analysis of plant operation principles in french Pressurized Water Reactor (PWR), we describe a NPP functional organisation. We propose to regard this NPP functional organisation as a specification for a multi-agent design. With a decentralised and distributed approach, we expect to improve the robustness of the whole control system. Our objective is to evaluate its efficiency by a prototype.
As far as some Intelligent Manufacturing Systems (IMS) are concerned, they are characterised, with more or less intensity, as being composed of intelligent, autonomous and co-operative units. Each unit holds a set of ...
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As far as some Intelligent Manufacturing Systems (IMS) are concerned, they are characterised, with more or less intensity, as being composed of intelligent, autonomous and co-operative units. Each unit holds a set of functional, decisional, informational and communication means. We believe that the suitable use of such means (and consequently the IMS means), is directly related with the ability that the units have to carry out decision-making processes, particularly those concerning the co-ordination of tasks in a co-operative way. In such a context, the "intelligence" of the units ascends in significance. This paper proposes an agent-based model as a way to face the lack of understanding and development of some intelligent aspects. Such model is mainly defined based on a modelling paradigm called Agent Oriented Programming Paradigm for Production Systems(AOP3S).
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