Soccer server: A tool for research on multiagent systems

This article describes Soccer Server, a simulator of the game of soccer designed as a benchmark for evaluating multiagent systems and cooperative algorithms. In real life, successful soccer teams require many qualities, such as basic ball control skills, the ability to carry out strategies, and teamwork. We believe that simulating such behaviors is a significant challenge for computer science, artificial intelligence, and robotics technologies. It is to promote the development of such technologies, and to help define a new standard problem for research, that we have developed Soccer Server. We demonstrate the potential of Soccer Server by reporting an experiment that uses the system to compare the performance of a neural network architecture and a decision tree algorithm at learning the selection of soccer play plans. Other researchers using Soccer Server to investigate the nature of cooperative behavior in a multiagent environment will have the chance to assess their progress at RoboCup-97, an international competition of robotic soccer to be held in conjunction with IJCAI-97. Soccer Server has been chosen as the official server for this contest.     

Automated Assistants for Analyzing Team Behaviors

Multi-agent teamwork is critical in a large number of agent applications, including training, education, virtual enterprises and collective robotics. The complex interactions of agents in a team as well as with other agents make it extremely difficult for human developers to understand and analyze agent-team behavior. It has thus become increasingly important to develop tools that can help humans analyze, evaluate, and understand team behaviors. However, the problem of automated team analysis is largely unaddressed in previous work. In this article, we identify several key constraints faced by team analysts. Most fundamentally, multiple types of models of team behavior are necessary to analyze different granularities of team events, including agent actions, interactions, and global performance. In addition, effective ways of presenting the analysis to humans is critical and the presentation techniques depend on the model being presented. Finally, analysis should be independent of underlying team architecture and implementation.We also demonstrate an approach to addressing these constraints by building an automated team analyst called ISAAC for post-hoc, off-line agent-team analysis. ISAAC acquires multiple, heterogeneous team models via machine learning over teams' external behavior traces, where the specific learning techniques are tailored to the particular model learned. Additionally, ISAAC employs multiple presentation techniques that can aid human understanding of the analyses. ISAAC also provides feedback on team improvement in two novel ways: (i) It supports principled what-if reasoning about possible agent improvements; (ii) It allows the user to compare different teams based on their patterns of interactions. This paper presents ISAAC's general conceptual framework, motivating its design, as well as its concrete application in two domains: (i) RoboCup Soccer; (ii) software agent teams participating in a simulated evacuation scenario. In the RoboCup domain, ISAAC was used prior to and during the RoboCup '99 tournament, and was awarded the RoboCup Scientific Challenge Award. In the evacuation domain, ISAAC was used to analyze patterns of message exchanges among software agents, illustrating the generality of ISAAC's techniques. We present detailed algorithms and experimental results from ISAAC's application.     

The ACTive Intervention in Hospice Interdisciplinary Team Meetings: Exploring Family Caregiver and Hospice Team Communication

This paper presents the theoretical framework and rationale for the ACTive intervention which proposes the use of video technology to facilitate patient and family participation in hospice interdisciplinary team meetings where plans of care are determined. It is surmised that patient and family involvement will improve communication and compliance in hospice care. An analysis of data from a pilot project of the ACTive intervention was conducted to explore active participation among family caregivers and the hospice team. Through the use of videophone technology caregivers participated in video‐recorded team meetings. The actual communication behaviors of caregivers and team members were analyzed for active participation. Findings revealed that team–prompted caregiver participation was most common, however, team use of supportive talk in this context was considerably less frequent. The study also found that the team's use of active participation behaviors elicits caregiver active participation behaviors. The results of this study suggest the intervention was an effective way to involve family caregivers as active participants in the designing of care for their loved one. Findings also suggest that hospice staff would benefit from education and training on best practices for communicating with caregivers in the team meeting setting.     

基于概率推理的入侵意图识别研究

攻击者的入侵行为背后往往蕴含着攻击者的目标和意图,据此提出了入侵意图识别的层次化模型。为了处理网络环境中的不确定性信息,提出了基于概率推理的入侵意图识别算法,并在此基础上预测攻击者的后续攻击规划和目标,从而起到提前预警的作用。根据网络安全事件、目标和意图之间的因果关系建立的贝叶斯网络能够描述和处理并发意图识别问题。试验证明了该方法的可行性和有效性。     

REACTIVE AGENT DESIGN FOR INTELLIGENT TUTORING SYSTEMS

This paper presents a new approach to the analysis and design of intelligent tutoring systems (ITS), based on reactive principles and cognitive models, this way leading to multiagent architecture. In these kinds of models, the analysis problem is treated bottom-up, as opposed to that of traditional artificial intelligence (AI), i.e., top down. We present one ITS example called Makatsina (meaning tutor in TOTONACA, a Mexican pre-Columbian language), constructed according to this approach, which teaches the skills necessary to solve the truss analysis problem by the method of joints. This learning domain is an integration skill. The classical ITS work is based on explicit goals and an internal representation of the environment. The new approach has reactive agents which have no representation of their environment and act using a stimulus response behavior type. In this way they can respond to the present state of the environment in which they are embedded. With these elements, errors, and teaching plans, each agent behaves as an expert assistant that is able to handle different teaching methods. Reactive agent programming is found to be simple because agents have simple behaviors. The difficulty lies in the interaction mechanism analysis and design between the environment and the intelligent reactive system.     

Implementing agent teams in dynamic multiagent environments

Teamwork is becoming increasingly critical in multiagent environments ranging from virtual environments for training and education, to information integration on the internet, to potential multirobotic space missions. Teamwork in such complex, dynamic environments is more than a simple union of simultaneous individual activity, even if supplemented with preplanned coordination. Indeed, in these dynamic environments, unanticipated events can easily cause a breakdown in such preplanned coordination. The central hypothesis in this article is that for effective teamwork, agents should be provided explicit representation of team goals and plans, as well as an explicit representation of a model of teamwork to support the execution of team plans. In our work, this model of teamwork takes the form of a set of domain independent rules that clearly outline an agent's commitments and responsibilities as a participant in team activities, and thus guide the agent's social activities while executing team plans. This article describes two implementations of agent-teams based on the above principles, one for a realworld helicopter combat simulation, and one for the RoboCup soccer simulation. The article also provides a preliminary comparison of the two agent-teams to illustrate some of the strengths and weaknesses of RoboCup as a common test bed for multiagent systems.     

Plan Execution Based on Active Perception: Adding Hints to Plans

In this paper we present a complete control architecture for a mobile robot which enables it to achieve a set of proposed goals with a high degree of autonomy and to react to the changing environment in real time. Autonomy and robustness are achieved through careful selection and incremental implementation of a set of basic Motor-Behaviors that interpret the sensor readings (sonar, vision and odometric sensors) and actuate the motors. The plan is provided by a user, and is expressed as a sequence of goals and a series of hints on how to achieve them. These hints are based on the user's knowledge of the environment and of the robot's behavioral and perceptual abilities. A new set of behaviors, called Conductor-Behaviors, which inspect and modify Motor-Behaviors' attributes, have been introduced in order to link the robot's Motor-Behaviors to the user's plan. Finally, a canonical set of symbols, attached to the Motor-Behaviors, serves as well grounded symbols that the user can utilize to express the plans. We also report experimental results with a real robot that demonstrate how plans expressed as goals and hints to achieve them improve the robot's performance.     

一种基于矩阵度量的缺陷管理流程的改进与实践

本文在分析软件过程中缺陷类型、缺陷注入、缺陷识别的基础上,对传统缺陷管理流程进行改进,增加了缺陷排除有效性的度量方法;然后提出一种实用的软件缺陷管理流程,建立了一个以软件缺陷生命周期为基础的度量模型,并给出了相应的缺陷矩阵度量方法;最后把该缺陷管理流程和度量方法应用在某公司的两个软件项目中,对各阶段的缺陷进行了度量,经实践和数据分析得出,运用此缺陷管理流程和度量方法可以为开发团队设定具体阶段目标和质量计划提供数据基础,为过程控制、过程评价、持续改进等提供量化管理的基础,表明本文改进后的缺陷管理流程和度量方法模型是有效的。     

Resilience and vulnerability of small flexible crisis response teams: implications for training and preparation

Following the Asian Tsunami of 2004 and during the Israel–Lebanon Crisis of 2006, Sweden sent small crisis response teams to support civilians. The small size of the teams, combined with situations that did not always play out according to expectations and plans, presented a challenge to their resilience—their ability to adapt to circumstances outside of plans made in advance. In this paper, we analyze the experiences of 14 members of Swedish field teams involved in the crises response, based on focus group discussions. We describe a cycle of preparing for role improvisation, of taking improvised roles, of working in them, and of getting out of them when they are no longer a benefit. The discussions revealed that although role improvisation was seen as necessary to get the work done, they also saw a need to manage negative side effects and vulnerabilities of role improvisation in various ways. We discuss training goals based on their experiences, to address perceived strengths and vulnerabilities of role improvisation. We also discuss factors affecting role improvisation, such as a resilience climate of shared attitudes. Our results can be useful for organizations that have or that plan to adopt flexible crisis response teams. Our results can also be of interests to a more general audience with an interest in how practices necessary for resilience can bring negative side effects, for instance, resilience loss in the organization after an initial adaptive stage.     

Sharing your view: A distributed user interface approach for reviewing emergency plans

Emergency planning is an ongoing activity in which a multidisciplinary group of experts intermittently collaborate to define the most appropriate response to risks. One of the most important tasks of emergency planning is the review of plans as a way of maintaining, refining, and improving them. This review of plans is based on exchanging knowledge and experiences in order to take into account different perspectives and generate alternative solutions. An exploratory case study carried out within municipal organizations has disclosed how the application of rigid plan reviewing practices hinders team creativity and, consequently, effective decision-making. This paper presents a computer-based collaborative environment aimed at supporting unstructured team discussion during the post-hoc review of emergency plan. This collaborative environment allows emergency planning team members to share their view in a free manner by interacting with user interface components distributed across several input and output dimensions. The usage of the environment has proved how the application of new interactive technologies can create more dynamic work settings, fostering team creativity.     

A Resource Logic for Multi-Agent Plan Merging

In a multi-agent system, agents are carrying out certain tasks by executing plans. Consequently, the problem of finding a plan, given a certain goal, has been given a lot of attention in the literature. Instead of concentrating on this problem, the focus of this paper is on cooperation between agents which already have constructed plans for their goals. By cooperating, agents might reduce the number of actions they have to perform in order to fulfill their goals. The key idea is that in carrying out a plan an agent possibly produces side products that can be used as resources by other agents. As a result, an other agent can discard some of its planned actions. This process of exchanging products, called plan merging, results in distributed plans in which agents become dependent on each other, but are able to attain their goals more efficiently. In order to model this kind of cooperation, a new formalism is developed in which side products are modeled explicitly. The formalism is a resource logic based on the notions of resource, skill, goal, and service. Starting with some resources, an agent can perform a number of skills in order to produce other resources which suffice to achieve some given goals. Here, a skill is an elementary production process taking as inputs resources satisfying certain constraints. A service is a serial or parallel composition of skills acting as a program. An operational semantics is developed for these services as programs. Using this formalism, an algorithm for plan merging is developed, which is anytime and runs in polynomial time. Furthermore, a variant of this algorithm is proposed that handles the exchange of resources in a more flexible way. The ideas in the paper will be illustrated by an example from public transportation.     

Overcoming impediments to virtual team effectiveness

The term virtual team denotes an organizational team whose members rarely meet face to face but who nevertheless perform interdependent tasks in pursuit of collective goals. This article identifies the unique aspects of virtual teams that generate major barriers to their effectiveness, and suggests ways in which these may be either overcome or mitigated. A process‐oriented model of virtual team effectiveness is presented, identifying issues associated with the development of transactive memory systems, work engagement, and collective efficacy as major challenges to virtual team effectiveness. These issues are illustrated with reference to the experience of virtual teams within a minerals processing firm. Finally, the authors discuss aspects of virtual team leadership and team climate that may help overcome some of the potential process losses associated with virtual teamwork. © 2008 Wiley Periodicals, Inc.     

Understanding the attitudes,knowledge sharing behaviors and task performance of core developers: A longitudinal study

ContextPrior research has established that a few individuals generally dominate project communication and source code changes during software development. Moreover, this pattern has been found to exist irrespective of task assignments at project initiation.ObjectiveWhile this phenomenon has been noted, prior research has not sought to understand these dominant individuals. Previous work considering the effect of team structures on team performance has found that core communicators are the gatekeepers of their teams’ knowledge, and the performance of these members was correlated with their teams’ success. Building on this work, we have employed a longitudinal approach to study the way core developers’ attitudes, knowledge sharing behaviors and task performance change over the course of their project, based on the analysis of repository data.MethodWe first used social network analysis (SNA) and standard statistical analysis techniques to identify and select artifacts from ten different software development teams. These procedures were also used to select central practitioners among these teams. We then applied psycholinguistic analysis and directed content analysis (CA) techniques to interpret the content of these practitioners’ messages. Finally, we inspected these core developers’ activities as recorded in system change logs at various points in time during systems’ development.ResultsAmong our findings, we observe that core developers’ attitudes and knowledge sharing behaviors were linked to their involvement in actual software development and the demands of their wider project teams. However, core developers appeared to naturally possess high levels of insightful characteristics, which became evident very early during teamwork.ConclusionsProject performance would likely benefit from strategies aimed at surrounding core developers with other competent communicators. Core developers should also be supported by a wider team who are willing to ask questions and challenge their ideas. Finally, the availability of adequate communication channels would help with maintaining positive team climate, and this is likely to mitigate the negative effects of distance during distributed developments.     

Automatic generation of communication and teamwork within multi-agent teams

Teamwork and communication are two important processes within multi-agent systems designed to act in a coherent and coordinated manner. Modeling teamwork involves interleaving steps within shared plans that will allow agents to work together towards common goals. These steps involve reasoning about roles, responsibilities, and joint-intentions in order to coordinate activity amongst individuals. Communication facilitates teamwork. There are various complex forms of communication such as synchronization, coordination, and cooperation that allow for members of teams to use teamwork to their advantage. Explicitly defining every possible communication point within a team plan is too cumbersome and inflexible. In this paper, we describe a method to automatically decompose a team plan into a collection of individual agent plans, inserting all of the necessary communication points needed to properly generate coordinated behavior. This approach could be used to more accurately and easily model teamwork in multi-agent systems.     

Trajectory design and control for aggressive formation flight with quadrotors

In this work we consider the problem of controlling a team of micro-aerial vehicles moving quickly through a three-dimensional environment while maintaining a tight formation. The formation is specified by shape vectors which prescribe the relative separations and bearings between the robots. To maintain the desired shape, each robot plans its trajectory independently based on its local information of other robot plans and estimates of states of other robots in the team. We explore the interaction between nonlinear decentralized controllers, the fourth-order dynamics of the individual robots, time delays in the network, and the effects of communication failures on system performance. Simulations as well as an experimental evaluation of our approach on a team of quadrotors suggests that suitable performance is maintained as the formation motions become increasingly aggressive and as communication degrades.     

实验室能力验证管理信息系统的设计与实现

实验室能力验证是对实验室检测能力和管理状况进行客观考核的一种方法。通过对实验室能力验证过程的分析研究,运用PHP技术,以MySQL为后台数据库,设计并实现了基于B/S模式的实验室能力验证管理信息系统。验证活动的组织者通过该系统发布验证计划,分配测试项目,管理测试数据,评定测试结果,接收测试反馈。该系统优化了繁杂的验证过程,提高了验证管理的信息化水平和工作效率,增强了实验室的自检和自控能力,有利于实验室的可持续发展。     

Plan recognition for interface agents

Interface agents are computer programs that provide personalized assistance to a user dealing with computer based applications. By understanding the tasks the user performs in a software application an interface agent could be aware of the context that represents the user’s focus of attention at each particular moment. With this purpose, plan recognition aims at identifying the plans or goals of a user from the tasks he (for simplicity, we use “he” to refer to the user, but we do not mean any distinctions about sexes) performs. A prerequisite for the recognition of plans is knowledge of a user’s possible tasks and the combination of these tasks in complex task sequences, which describes typical user behavior. Plan recognition will enable an interface agent to reason about what the user might do next so that it can determine how to assist him. In this work we present the state of the art in Plan Recognition, paying special attention to the features that make it useful to interface agents. These features include the ability to deal with uncertainty, multiple plans, multiple interleaved goals, overloaded tasks, noisy tasks, interruptions and the capability to adapt to a particular user.     

The effects of knowledge management systems on emergent teams: towards a research model

This article describes how knowledge management systems can enhance the effectiveness of teams that analyze complex, non-recurring problems by improving the way that team composition evolves. Knowledge management systems reduce the costs of searching for specialized knowledge resources, making it more likely that teams will incorporate a diversity of knowledge. Drawing on the concept of requisite variety, this article argues that increases in team knowledge variety lead to improvements in the effectiveness of the solutions generated by a team, which in turn enhance their organization's adaptive ability. This process also reinforces the existing distribution of knowledge within the organization, increasing employee specialization. The author develops a series of propositions and combines them into a research model from which he draws implications for researchers and managers.     

Unified Behavior Framework for Reactive Robot Control

Behavior-based systems form the basis of autonomous control for many robots. In this article, we demonstrate that a single software framework can be used to represent many existing behavior based approaches. The unified behavior framework presented, incorporates the critical ideas and concepts of the existing reactive controllers. Additionally, the modular design of the behavior framework: (1) simplifies development and testing; (2) promotes the reuse of code; (3) supports designs that scale easily into large hierarchies while restricting code complexity; and (4) allows the behavior based system developer the freedom to use the behavior system they feel will function the best. When a hybrid or three layer control architecture includes the unified behavior framework, a common interface is shared by all behaviors, leaving the higher order planning and sequencing elements free to interchange behaviors during execution to achieve high level goals and plans. The framework’s ability to compose structures from independent elements encourages experimentation and reuse while isolating the scope of troubleshooting to the behavior composition. The ability to use elemental components to build and evaluate behavior structures is demonstrated using the Robocode simulation environment. Additionally, the ability of a reactive controller to change its active behavior during execution is shown in a goal seeking robot implementation.     

基于Markov对策的多智能体协调方法及其在Robot Soccer中的应用

提出了一种分层的基于Markov对策的多智能体协调方法,根据多智能体之间的竞争和合作的关系,高层采用零和Markov对策解决与对手之间的竞争,低层采用团队Markov对策完成与团队内部的合作．通过在Robot Soccer中的应用和实验,说明了基于Markov对策的多智能体协调方法优于传统的多智能体学习．