Safe Multirobot Navigation Within Dynamics Constraints

This paper introduces a refinement of the classical sense-plan-act objective maximization method for setting agent goals, a real-time randomized path planner, a bounded acceleration motion control system, and a randomized velocity-space search for collision avoidance of multiple moving robotic agents. We have found this approach to work well for dynamic and unpredictable domains requiring real-time response and flexible coordination of multiple agents. First, the approach employs randomized search for objective maximization and motion planning, allowing real-time or any-time performance. Next, a novel cooperative safety algorithm is employed which respects agent dynamics limitations while also preventing collisions with static obstacles or other participating agents. An implementation of our multilayer approach has been tested and validated on real robots, forming the basis for an autonomous robotic soccer team.     

A Stochastic and Dynamic Vehicle Routing Problem with Time Windows and Customer Impatience

In this paper, we study the problem of designing motion strategies for a team of mobile agents, required to fulfill request for on-site service in a given planar region. In our model, each service request is generated by a spatio-temporal stochastic process; once a service request has been generated, it remains active for a certain deterministic amount of time, and then expires. An active service request is fulfilled when one of the mobile agents visits the location of the request. Specific problems we investigate are the following: what is the minimum number of mobile agents needed to ensure that a certain fraction of service requests is fulfilled before expiration? What strategy should they use to ensure that this objective is attained? This problem can be viewed as the stochastic and dynamic version of the well-known vehicle routing problem with time windows. We also extend our analysis to the case in which the time service requests remain active is itself a random variable, describing customer impatience. The customers’ impatience is only known to the mobile agents via prior statistics. In this case, it is desired to minimize the fraction of service requests missed because of impatience. Finally, we show how the routing strategies presented in the paper can be executed in a distributed fashion.     

An architecture and protocol for communications satellite constellations regarded as multi-agent systems

This paper presents an architecture for satellites regarded as intercommunicating agents. The architecture is based upon a postmodern paradigm of artificial intelligence in which represented knowledge is regarded as text, inference procedures are regarded as social discourse and decision-making conventions, and the semantics of representations is grounded in the situated behaviour and activity of agents. A particular protocol is described for agent participation in distributed search and retrieval operations conducted as joint activities.     

Optimal reliable relay selection in multiuser cooperative relaying networks

In this paper, we investigate the problem of optimal reliable relay selection in multiuser cooperative wireless networks in the presence of malicious relay nodes. A general discrete time queueing model for such networks is introduced which takes into account the dynamic variations of the channel state, the dynamic malicious behaviour of relay nodes as well as stochastic arrival of data packets into the system. The model consists of a set of mobile users, one destination node and a set of relay nodes which may be either mobile or fixed. The system uses the benefit of cooperative diversity by relaying in the decode and forward mode. We assume that each user either transmits its packets directly to the destination (direct mode) or transmits them with the cooperation of a selected relay node (cooperative mode). It is assumed that a centralized network controller manages the relay selection process in the system. At each time slot, a malicious relay node in the system may behave spitefully and refuse to cooperate with a user deliberately when it is selected to cooperate with that user. A malicious relay node usually acts stochastically to hide its malicious behaviour for longer time. In such a system, at each time slot the network controller should decide whether a user has to cooperate with any relay node or not and if so, which relay node must be selected for cooperation. First, we show that the malicious behaviour of relay nodes makes the stable throughput region shrink. Then, we propose a throughput optimal secure relay selection policy that can stabilize the system for all the arrival rate vectors strictly inside the network stability region. We show that the optimal policy is equivalent to finding the maximum weighted matching in a weighted bipartite graph at each time slot. Finally, we use simulations to compare the performance of the proposed policy with that of four other sub-optimal policies in terms of average queue occupancy (or queueing delay).     

一种基于多主体模糊知识交换的动态网络路由方法

路由是通信网络中重要的研究课题,但对于高度动态网络环境,现有的许多路由方法仍存在一些局限性。本文将多Agent(主体)迁移合作系统应用于解决动态网络路由问题,提出了基于模糊知识的多Agent合作模型和用于计算路由的基础合作算法,并讨论了影响系统的几个关键因素。通过对动态网络仿真的试验研究,分析了系统的性能开销特性和合作策略。研究结果表明,所提出理论模型和算法适合于解决动态网络的路由问题,并且能提高路由系统的响应性能。     

A Survey of Cooperative Games for Cognitive Radio Networks

Cooperative cognitive radio networks are new cognitive radio paradigm. Cooperative communication approaches, such as cooperative spectrum sensing and cooperative spectrum sharing, are playing key roles in the development of cognitive radio networks. To achieve the high performance, a cooperative cognitive communication framework is often used to model various cooperative spectrum sensing or sharing scenarios. However, its implementation faces numerous challenges due to the complexity of mobility and traffic models, the needs of dynamic spectrum access, the heterogeneous requirements from different users, and the distributed structure of the network. Fortunately, cooperative game theory can be used to formulate and model the interactions among licensed and unlicensed users for spectrum sensing and spectrum sharing to efficiently allocate spectrum resource in the highly dynamic and distributed radio environment. In this paper, we first present the cooperative communication technologies and describe their existing challenges, then introduce different game solutions, after that, we discuss several cooperative game strategies, and analyze the associated their applications in cognitive radio networks, at final, some open directions for future research on economic strategies in cooperative communication in cognitive radio networks are proposed.     

Partnering on construction projects: a study of the relationshipbetween partnering activities and project success

Project partnering has generated considerable attention in the construction industry as a means for transforming hostile, adversarial owner-contractor relationships into a more collaborative, productive team. Empirical support for partnering, however, is limited. The present study used mailed questionnaire data to examine the relationship between specific partnering related activities and project success for 291 construction projects. All of the major partnering activities were found to be positively related to at least one of the measures of project success. The findings suggest that a comprehensive approach be applied to partnering on construction projects and that top management support for teamwork across organizations is critical to success     

一种新颖的多agent强化学习方法

提出了一种综合了模块化结构、利益分配学习以及对手建模技术的多agent强化学习方法,利用模块化学习结构来克服状态空间的维数灾问题,将Q-学习与利益分配学习相结合以加快学习速度,采用基于观察的对手建模来预测其他agent的动作分布.追捕问题的仿真结果验证了所提方法的有效性.     

Teamwork and Collaboration in Cognitive Wireless Networks

This article looks at the principles and significant potential of teamwork in cognitive networks. These concepts represent a new evolutionary stage in the development of cognitive radio and cognitive networks, where wireless communication progresses from an individual, device-centric approach toward group and team behavior. This creates the potential for more effective and more robust communication solutions when deemed necessary. The key elements of effective cognitive network teamwork are introduced in this article. These include group formation, distributed co-ordination, goal and role identification, accountability, and reward mechanisms for the outcomes of team behavior. The value of the group as a whole can be increased rather than individual gain for only a single device. Focusing on an early experimental cognitive network teamwork testbed designed by CTVR, this article outlines the potential of developing cognitive networks that can work as a team. Potential applications and market opportunities for this technology also are described.     

Non‐inferior Nash strategies for routing control in parallel‐link communication networks

We consider a routing control problem of two‐node parallel‐link communication network shared by competitive teams of users. Each team has various types of entities (traffics or jobs) to be routed on the network. The users in each team cooperate for the benefit of their team so as to achieve optimal routing over network links. The teams, on the other hand, compete among themselves for the network resources and each has an objective function that relates to the overall performance of the network. For each team, there is a centralized decision‐maker, called the team leader or manager, who coordinates the routing strategies among all entities in his team. A game theoretic approach to deal with both cooperation within each team and competition among the teams, called the Non‐inferior Nash strategy, is introduced. Considering the roles of a group manager in this context, the concept of a Non‐inferior Nash strategy with a team leader is introduced. This multi‐team solution provides a new framework for analysing hierarchically controlled systems so as to address complicated coordination problems among the various users. This strategy is applied to derive the optimal routing policies for all users in the network. It is shown that Non‐inferior Nash strategies with a team leader is effective in improving the overall network performance. Various types of other strategies such as team optimization and Nash strategies are also discussed for the purpose of comparison. Copyright © 2005 John Wiley & Sons, Ltd.     

Connectivity management in mobile ad hoc networks using particle swarm optimization

This paper proposes a dynamic mobile ad hoc network (MANET) management system to improve network connectivity by using controlled network nodes, called agents. Agents have predefined wireless communication capabilities similar to the other nodes in the MANET, however their movements, and thus their locations, are dynamically determined to optimize network connectivity. A new approach to measuring connectivity using a maximum flow formulation is proposed – this is both responsive and tractable. Furthermore, users’ locations are predicted for several time steps ahead and this is shown to improve network connectivity over the network operation period. A particle swarm optimization (PSO) algorithm uses the maximum flow objective to choose optimal locations of the agents during each time step of network operation. The proposed MANET management system is rigorously tested on numerous static and dynamic problems. Computational results show that the proposed approach is effective in improving the connectivity of MANETs and predicting movements of user nodes and deploying agents accordingly significantly improves the overall performance of a MANET.     

Cooperative Path Dynamic Planning Model of UCAV Team Based on Global Optimization Method

Cooperative path dynamic planning of a UCAV (unmanned combat air vehicle) team not only considers the capability of task requirement of single UCAV, but also considers the cooperative dynamic connection among members of the UCAV team. A cooperative path dynamic planning model of the UCAV team by applying a global optimization method is discussed in this paper and the corresponding model is built and analyzed. By the example simulation, the reasonable result acquired indicates that the model could meet dynamic planning demand under the circumstance of membership functions. The model is easy to be realized and has good practicability.     

Incremental Coevolution With Competitive and Cooperative Tasks in a Multirobot Environment

Coevolution has been receiving increased attention as a method for simultaneously developing the control structures of multiple agents. Our ultimate goal is the mutual development of skills through coevolution. The coevolutionary process is, however, often prone to settle into suboptimal strategies. The key to successful coevolution has thus far been unclear. This paper discusses how several robots can emerge cooperative and competitive behavior through coevolutionary processes. In order to realize successful coevolution, we propose two ideas: multiple schedules for incremental evolution and fitness sharing based on the method of importance sampling. To examine this issue, we conducted a series of computer simulations. We have chosen a simplified soccer game consisting of two or three robots as a testbed for analyzing a problem in which both competitive and cooperative tasks are involved. We show that the proposed fitness evaluation allows robots to evolve robust behaviors in cooperative and competitive situations.     

Ontology mapping for the interoperability problem in network management

Interoperability between different network management domains, heterogeneous devices, and various management systems is one of the main requirements for managing complex enterprise services. While substantial advances have been made in low-level device and data interoperability using common data formats and specifications such as simple network management protocol's (SNMP's) SMI and TMF's SID, various interoperability issues including semantic interoperability offer interesting research challenges. While semantic interoperability is a difficult problem in its own right, the semantic web that incorporates intelligent agents necessitates an interoperability solution requiring agents to communicate unambiguously and reason intelligently to perform cooperative management tasks. Agents need a formal representation of knowledge; an ontology is capable of modeling the rich semantics of the managed environment (and especially, relationships between managed entities) so that agents can act on them. This paper presents an ontology-driven approach for solving the semantic interoperability problem in the management of enterprise services, illustrated here with a router configuration management application.     

State-based modeling and object extraction from echocardiogram video

In this paper, we propose a hierarchical state-based model for representing an echocardiogram video. It captures the semantics of video segments from dynamic characteristics of objects present in each segment. Our objective is to provide an effective method for segmenting an echo video into view, state, and substate levels. This is motivated by the need for building efficient indexing tools to support better content management. The modeling is done using four different views, namely, short axis, long axis, apical four chamber, and apical two chamber. For view classification, an artificial neural network is trained with the histogram of a region of interest of each video frame. Object states are detected with the help of synthetic M-mode images. In contrast to traditional single M-mode, we present a novel approach named sweep M-mode for state detection. We also introduce radial M-mode for substate identification from color flow Doppler 2-D imaging. The video model described here represents the semantics of video segments using first-order predicates. Suitable operators have been defined for querying the segments. We have carried out experiments on 20 echo videos and compared the results with manual annotation done by two experts. View classification accuracy is 97.19%. Misclassification error of the state detection stage is less than 13%, which is within acceptable range since only frames at the state boundaries are found to be misclassified.     

Construction of Nonlinear Dynamic MEMS Component Models Using Cosserat Theory

This paper presents a new modelling method for MEMS components based on the Cosserat theory. By constructing Cosserat rod elements, generating symbolic code and developing numeric code in VHDL-AMS for selected demonstrators, we are able to effectively simulate and predict the essential linear and nonlinear behaviour in estimating system performance and guiding the reliability verification process. The simplicity of the Cosserat approach follows from the possibility to formulate interconnected slender components in terms of a network of quasi-rigid bodies (Cosserat elements). This modularization fits well into the behavioural modelling where a relatively low degree of freedom is needed to capture salient features of the system. Furthermore, the manner in which Cosserat elements and their interactions are formulated makes this method ideally suited for nonlinear dynamic simulations in the presence of large deflections.     

A Game Theoretical Framework for Dynamic Pricing-Based Routing in Self-Organized MANETs

In self-organized mobile ad hoc networks (MANETs) where each user is its own authority, fully cooperative behaviors, such as unconditionally forwarding packets for each other or honestly revealing its private information, cannot be directly assumed. The pricing mechanism is one way to provide incentives for the users to act cooperatively by awarding some payment for cooperative behaviors. In this paper, we consider efficient routing in self-organized MANETs and model it as multi-stage dynamic pricing games. A game theoretical framework for dynamic pricing-based routing in MANETs is proposed to maximize the sender/receiver?s payoff by considering the dynamic nature of MANETs. Meanwhile, the forwarding incentives of the relay nodes can also be maintained by optimally pricing their packet-forwarding services based on the auction rules and introducing the Cartel Maintenance enforcing mechanism. The simulation results illustrate that the proposed dynamic pricing-based routing approach has significant performance gains over the existing static pricing approaches.     

A Drug‐Self‐Gated Mesoporous Antitumor Nanoplatform Based on pH‐Sensitive Dynamic Covalent Bond

To achieve on‐demand drug release, mesoporous silica nanocarriers as antitumor platforms generally need to be gated with stimuli‐responsive capping agents. Herein, a “smart” mesoporous nanocarrier that is gated by the drug itself through a pH‐sensitive dynamic benzoic–imine covalent bond is demonstrated. The new system, which tactfully bypasses the use of auxiliary capping agents, could also exhibit desirable drug release at tumor tissues/cells and enhanced tumor inhibition. Moreover, a facile dynamic PEGylation via benzoic–imine bond further endows the drug‐self‐gated nanocarrier with tumor extracellular pH‐triggered cell uptake and improves therapeutic efficiency in vivo. In short, the paradigm shift in capping agents here will simplify mesoporous nanomaterials as intelligent drug carriers for cancer therapy. Moreover, the self‐gated strategy in this work also shows general potential for self‐controlled delivery of natural biomolecules, for example, DNA/RNA, peptides, and proteins, due to their intrinsic amino groups.     

“信号与系统”合作性学习教学策略设计

本文以“信号与系统”课程教学为例，描述了以教师为主导、学生为主体的合作性学习教学策略。笔者围绕着课程教学的知识目标及团队合作能力、运用仿真工具的建模能力、线性系统分析能力等能力培养目标，给出了集知识传授与能力培养为一体并体现项目实施过程的课程教学体系，设计趣味性的研讨项目及Matlab仿真项目，描述了合作性学习的评价方...