多代理技术在船体装配CAPP系统的应用

本文介绍了多代理技术在船体装配 CAPP系统中应用 .包括 :船体装配 CAPP系统的结构 ,Agent之间的通讯 ,Agent表达方法、提供的函数功能描述 ,以及各工艺代理的功能描述和封装实例 ;采用多代理技术的船体装配 CAPP系统可以生成满足工厂要求的装配工艺文件、工艺定额和材料定额

分布式多机器人装配系统任务合作规划算法研究

:综述了多机器人系统任务规划的研究 ,介绍了基于 Agent的分布协作式多机器人装配系统 ,给出了分布式多机器人系统任务协商规划算法 ,采用了改进的合同网协议方法。针对多机器人任务规划算法的软件实现 ,采用了先进的分布式对象技术 ,介绍了算法的具体实现方法

面向装配作业的多机器人合作协调系统

分布、自主、协调与合作是多机器人系统的发展趋势。本文作者在研究易于协调合作的多机器人系统的基础上，采用分层递阶和多Ａｇｅｎｔ概念，构造了一个装配系统－ＭＲＯＣＡＳ系统。该系统具有任务自动建模分解，快速重组、良好柔性、友好人机界面，各机器人具有一定自主能力等特点，它实现了在较复杂环境下快速完成装配作业。

一个多智能体机器人协作装配系统

介绍了一个基于多智能体概念实现的多机器人协作装配系统——ＭＲＣＡＳ（Ｍｕｌｔｉ－ＲｏｂｏｔＣｏｏｐｅｒａｔｉｖｅＡｓｓｍｂｌｙＳｙｓｔｅｍ）。该系统由组织级计算机、三台工业机器人和一台全方位移动小车（ＯＤＶ）组成，采用分层递阶体系结构。利用ＭＲＣＡＳ系统进行了多机器人协作装配的实验：在ＯＤＶ装配平台上，四台机器人合作装配一个大型桁架式工件。该工件具有多种装配构型，但任何一台机器人不能独立完成装配。

KQML在多智能代理CAPP系统中的应用

KQML是目前多智能代理系统中广泛采用的通讯规范之一,它规定了标准格式来支持代理间的实时通讯。本文从理论和技术的角度阐述了KQML规范的内容、功能和基本结构,并把KQML规范应用在基于智能代理技术的CAPP系统中,圆满解决了系统的通讯问题,加强了系统的灵活性和稳定性。

基于多智能体的制造系统生产控制建模研究

为提高制造系统生产控制的性能,建立了基于多智能体系统的混合控制模型。该模型把生产控制系统分为管理智能体层、单元智能体层和执行智能体层。管理智能体层负责调度和协调各单元智能体,并对所有智能体进行管理;单元智能体层中的各单元智能体间通过公用数据库相互协作;执行智能体对制造系统内的硬件负责,它们根据局部的本地资源信息及当前状态,接收发布的任务,并对其求解。同一层次的智能体之间是分布式结构。采用基于多智能体的混合控制模式,提高了制造系统生产控制的实时性和灵活性。通过激光拼焊生产系统中的试验,验证了该模型的有效性。

水-盐-气天然流体的物理化学性质模拟与流体包裹体应用研究

Natural fluids with water-salt-gas are often found in every sphere of the Earth, whose physicochemical properties and geochemical behaviors are complicated. To study these properties and behaviors turns out to be one of the challenging issues in geosciences. Traditional approaches mainly depend on experiments and observations. However, it is impossible to obtain a large number of data covering a large T-P space of the Earth by experimental methods in the near future, which will hinder the advance of the theoretical study. Therefore, it is important to model natural fluids by advanced theoretical methods, by which limited experimental data can be extended to a large temperature-pressure-composition space. Physicochemical models developed in this dissertation are not only more accurate, but also extend the applied T-P-m region of the experimental data of the multi-fluid systems by about two times. These models provide the new and accurate theoretical tools for the geochemical research, especially for the water-rock interactions and the study of the fluid inclusions. The main achievements can be summarized as follows: (1) A solubility model on components of natural gases is presented. The solubility model on the systems of CH4-H2O-NaCl, C2H6-H2O-NaCl or N2-H2O-NaCl takes advantage of modern physicochemical theory and methods, and is an improvement over previous models whose prediction and precision are relatively poor. The model can predict not only the gas solubility in liquid phase but also water content in the gas phase. In addition, it can predict gases (methane or nitrogen) solubility in seawater and brine. Isochores can be determined, which are very important in the interpretation of fluid inclusions. (2) A density model on common aqueous salt solutions is developed. The density models with high precision for common aqueous salt solutions (H2O-NaCl, H2O-LiCl, H2O-KCl, H2O-MgCl2, H2O-CaCl2, H2O-SrCl2 or H2O-BaCl2) are absent in the past. Previous density models are limited to the relatively small range of experimental data, and cannot meet the requirement of the study of natural fluids. So a general density model of the above systems is presented by us based on the international standard density model of the water. The model exceeds the other models in both precision and prediction. (3) A viscosity model on common aqueous alkali-chloride solutions is proposed. Dynamic viscosity of water-salt systems, an important physics variable, is widely used in three-dimension simulation of the fluids. But in most cases, due to the lack of viscosity models with a wide T-P range, the viscosity of aqueous salt solutions is replaced by that of the water, giving rise to a relatively large uncertainty. A viscosity model with good prediction for the systems (H2O-NaCl, H2O-LiCl or H2O-KCl) is presented on the base of the international standard viscosity model of water and the density model developed before. (4) Equation of State applied in fluid inclusions. The best Equations of State in the world developed by others or us recently are applied in the study of the fluid inclusions. Phase equilibria and isochores of unitary system (e.g. H2O, CO2, CH4, O2, N2, C2H6 or H2S), binary H2O-NaCl system and ternary H2O-CH4-NaCl system are finished. From these programs and thermodynamic equations of coexisting ores, the physicochemical conditions before or after the deposits form can be determined. To some extent, it is a better tool.

单（多）井抽灌对浅部地温场的影响研究

The technique of energy extraction using groundwater source heat pumps, as a sustainable way of low-grade thermal energy utilization, has widely been used since mid-1990's. Based on the basic theories of groundwater flow and heat transfer and by employing two analytic models, the relationship of the thermal breakthrough time for a production well with the effect factors involved is analyzed and the impact of heat transfer by means of conduction and convection, under different groundwater velocity conditions, on geo-temperature field is discussed.A mathematical model, coupling the equations for groundwater flow with those for heat transfer, was developed. The impact of energy mining using a single well system of supplying and returning water on geo-temperature field under different hydrogeological conditions, well structures, withdraw-and-reinjection rates, and natural groundwater flow velocities was quantitatively simulated using the finite difference simulator HST3D. Theoretical analyses of the simulated results were also made. The simulated results of the single well system indicate that neither the permeability nor the porosity of a homogeneous aquifer has significant effect on the temperature of the production segment provided that the production and injection capability of each well in the aquifers involved can meet the designed value. If there exists a lower permeable interlayer, compared with the main aquifer, between the production and injection segments, the temperature changes of the production segment will decrease. The thicker the interlayer and the lower the interlayer permeability, the longer the thermal breakthrough time of the production segment and the smaller the temperature changes of the production segment. According to the above modeling, it can also be found that with the increase of the aquifer thickness, the distance between the production and injection screens, and/or the regional groundwater flow velocity, and/or the decrease of the production-and-reinjection rate, the temperature changes of the production segment decline. For an aquifer of a constant thickness, continuously increase the screen lengths of production and injection segments may lead to the decrease of the distance between the production and injection screens, and the temperature changes of the production segment will increase, consequently.According to the simulation results of the single well system, the parameters, that can cause significant influence on heat transfer as well as geo-temperature field, were chosen for doublet system simulation. It is indicated that the temperature changes of the pumping well will decrease as the aquifer thickness, the distance between the well pair and/or the screen lengths of the doublet increase. In the case of a low permeable interlayer embedding in the main aquifer, if the screens of the pumping and the injection wells are installed respectively below and above the interlayer, the temperature changes of the pumping well will be smaller than that without the interlay. The lower the permeability of the interlayer, the smaller the temperature changes. The simulation results also indicate that the lower the pumping-and-reinjection rate, the greater the temperature changes of the pumping well. It can also be found that if the producer and the injector are chosen reasonably, the temperature changes of the pumping well will decline as the regional groundwater flow velocity increases. Compared with the case that the groundwater flow direction is perpendicular to the well pair, if the regional flow is directed from the pumping well to the injection well, the temperature changes of the pumping well is relatively smaller.Based on the above simulation study, a case history was conducted using the data from an operating system in Beijing. By means of the conceptual model and the mathematical model, a 3-D simulation model was developed and the hydrogeological parameters and the thermal properties were calibrated. The calibrated model was used to predict the evolution of the geo-temperature field for the next five years. The simulation results indicate that the calibrated model can represent the hydrogeological conditions and the nature of the aquifers. It can also be found that the temperature fronts in high permeable aquifers move very fast and the radiuses of temperature influence are large. Comparatively, the temperature changes in clay layers are smaller and there is an obvious lag of the temperature changes. According to the current energy mining load, the temperature of the pumping wells will increase by 0.7°C at the end of the next five years. The above case study may provide reliable base for the scientific management of the operating system studied.

Mobilized ad-hoc networks: A reinforcement learning approach

Research in mobile ad-hoc networks has focused on situations in which nodes have no control over their movements. We investigate an important but overlooked domain in which nodes do have control over their movements. Reinforcement learning methods can be used to control both packet routing decisions and node mobility, dramatically improving the connectivity of the network. We first motivate the problem by presenting theoretical bounds for the connectivity improvement of partially mobile networks and then present superior empirical results under a variety of different scenarios in which the mobile nodes in our ad-hoc network are embedded with adaptive routing policies and learned movement policies.

Deciding Isomorphisms of Simple Types in Polynomial Time

The isomorphisms holding in all models of the simply typed lambda calculus with surjective and terminal objects are well studied - these models are exactly the Cartesian closed categories. Isomorphism of two simple types in such a model is decidable by reduction to a normal form and comparison under a finite number of permutations (Bruce, Di Cosmo, and Longo 1992). Unfortunately, these normal forms may be exponentially larger than the original types so this construction decides isomorphism in exponential time. We show how using space-sharing/hash-consing techniques and memoization can be used to decide isomorphism in practical polynomial time (low degree, small hidden constant). Other researchers have investigated simple type isomorphism in relation to, among other potential applications, type-based retrieval of software modules from libraries and automatic generation of bridge code for multi-language systems. Our result makes such potential applications practically feasible.

Integration of micro- and macroscopic models for pedestrian evacuation simulation

Simulation of pedestrian evacuations of smart buildings in emergency is a powerful tool for building analysis, dynamic evacuation planning and real-time response to the evolving state of evacuations. Macroscopic pedestrian models are low-complexity models that are and well suited to algorithmic analysis and planning, but are quite abstract. Microscopic simulation models allow for a high level of simulation detail but can be computationally intensive. By combining micro- and macro- models we can use each to overcome the shortcomings of the other and enable new capability and applications for pedestrian evacuation simulation that would not be possible with either alone. We develop the EvacSim multi-agent pedestrian simulator and procedurally generate macroscopic flow graph models of building space, integrating micro- and macroscopic approaches to simulation of the same emergency space. By “coupling” flow graph parameters to microscopic simulation results, the graph model captures some of the higher detail and fidelity of the complex microscopic simulation model. The coupled flow graph is used for analysis and prediction of the movement of pedestrians in the microscopic simulation, and investigate the performance of dynamic evacuation planning in simulated emergencies using a variety of strategies for allocation of macroscopic evacuation routes to microscopic pedestrian agents. The predictive capability of the coupled flow graph is exploited for the decomposition of microscopic simulation space into multiple future states in a scalable manner. By simulating multiple future states of the emergency in short time frames, this enables sensing strategy based on simulation scenario pattern matching which we show to achieve fast scenario matching, enabling rich, real-time feedback in emergencies in buildings with meagre sensing capabilities.

Distributed belief revision as applied within a descriptive model of jury deliberations

Belief revision is a well-research topic within AI. We argue that the new model of distributed belief revision as discussed here is suitable for general modelling of judicial decision making, along with extant approach as known from jury research. The new approach to belief revision is of general interest, whenever attitudes to information are to be simulated within a multi-agent environment with agents holding local beliefs yet by interaction with, and influencing, other agents who are deliberating collectively. In the approach proposed, it's the entire group of agents, not an external supervisor, who integrate the different opinions. This is achieved through an election mechanism, The principle of "priority to the incoming information" as known from AI models of belief revision are problematic, when applied to factfinding by a jury. The present approach incorporates a computable model for local belief revision, such that a principle of recoverability is adopted. By this principle, any previously held belief must belong to the current cognitive state if consistent with it. For the purposes of jury simulation such a model calls for refinement. Yet we claim, it constitutes a valid basis for an open system where other AI functionalities (or outer stiumuli) could attempt to handle other aspects of the deliberation which are more specifi to legal narrative, to argumentation in court, and then to the debate among the jurors.

Belief revision as applied within a descriptive model of jury deliberations

Belief revision is a well-researched topic within Artificial Intelligence (AI). We argue that the new model of belief revision as discussed here is suitable for general modelling of judicial decision making, along with the extant approach as known from jury research. The new approach to belief revision is of general interest, whenever attitudes to information are to be simulated within a multi-agent environment with agents holding local beliefs yet by interacting with, and influencing, other agents who are deliberating collectively. The principle of 'priority to the incoming information', as known from AI models of belief revision, is problematic when applied to factfinding by a jury. The present approach incorporates a computable model for local belief revision, such that a principle of recoverability is adopted. By this principle, any previously held belief must belong to the current cognitive state if consistent with it. For the purposes of jury simulation such a model calls for refinement. Yet, we claim, it constitutes a valid basis for an open system where other AI functionalities (or outer stimuli) could attempt to handle other aspects of the deliberation which are more specific to legal narratives, to argumentation in court, and then to the debate among the jurors.

Strategies for water pollution control in Dhaka, Bangladesh: an institutional and economic analysis

This paper presents primary data based on research carried out as part of a large World Bank project. Results from our survey show that water pollution in Dhaka watershed has reached alarming levels and is posing significant threats to health and economic activity, particularly among the poor and vulnerable. Rice productivity in the watershed area, for example, has declined by 40% in recent years and vegetable cultivation in the riverbeds has been severely damaged. We also found significant correlation between water pollution and diseases such as jaundice, diarrhoea and skin problems. It was reported that the cost of treatment of skin diseases for one episode could be as high as 29% of the weekly earnings of poor households. Given the magnitude of the contamination problem, a multi-agent stakeholder approach was necessary to analyse the institutional and economic constraints that would need to be addressed in order to improve environmental management. This approach, in turn, enabled core strategies to be developed. The strategies were better understood around three types of actors in industrial pollution, i.e. (1) principal actors, who contribute directly to industrial pollution; (2) stakeholders, who exacerbate the situation by inaction; and (3) the potential actors in mitigation of water contamination. Within a carrot-and-stick framework, nine strategies leading to the strengthening of environmental management were explored. They aim at improving governance and transparency within public agencies and private industry through the setting up of incentive structures to advance compliance and enforcement of environmental standards. Civil society and the population at large are, on the other hand, encouraged to contribute actively to the mitigation of water pollution by improving the management of environmental information and by raising public awareness.

Query cost estimation through remote system contention states analysis over the Internet

Query processing over the Internet involving autonomous data sources is a major task in data integration. It requires the estimated costs of possible queries in order to select the best one that has the minimum cost. In this context, the cost of a query is affected by three factors: network congestion, server contention state, and complexity of the query. In this paper, we study the effects of both the network congestion and server contention state on the cost of a query. We refer to these two factors together as system contention states. We present a new approach to determining the system contention states by clustering the costs of a sample query. For each system contention state, we construct two cost formulas for unary and join queries respectively using the multiple regression process. When a new query is submitted, its system contention state is estimated first using either the time slides method or the statistical method. The cost of the query is then calculated using the corresponding cost formulas. The estimated cost of the query is further adjusted to improve its accuracy. Our experiments show that our methods can produce quite accurate cost estimates of the submitted queries to remote data sources over the Internet.