Automated text-based analysis for decision-making research

We present results from a study on constructing and evaluating a support tool for the extraction of patterns in distributed decision -making processes, based on design criteria elicited from a study on the work process involved in studying such decision-making. Specifically, we devised and evaluated an analysis tool for C² researchers who study simulated decision-making scenarios for command teams. The analysis tool used text clustering as an underlying pattern extraction technique and was evaluated together with C² researchers in a workshop to establish whether the design criteria were valid and the approach taken with the analysis tool was sound. Design criteria elicited from an earlier study with researchers (open-endedness and transparency) were highly consistent with the results from the workshop. Specifically, evaluation results indicate that successful deployment of advanced analysis tools requires that tools can treat multiple data sources and offer rich opportunities for manipulation and interaction (open-endedness) and careful design of visual presentations and explanations of the techniques used (transparency). Finally, the results point to the high relevance and promise of using text clustering as a support for analysis of C² data.     

精梳棉车间棉卷自动运输系统开发

连接生产工序参与生产流程是移动机器人真正应用于车间提高生产效率的关键。根据精梳棉车间的工作环境,研制了基于开源机器人操作系统（ROS）的棉卷自动运输机器人系统。移动机器人应用激光传感器采集车间环境数据,采用Gmapping算法构建精梳棉车间地图,应用经典A^*和人工势场法融合的混合路径规划算法自主规划行驶路径,并采用视觉二维码技术实现生产设备前的精确定位。测试结果显示,在1 m/s安全速度下,棉卷运输机器人定位误差与航向偏差的平均绝对误差（MAE）分别小于5 cm和07°,完全满足在精梳棉车间内自主避障运动以及在生产设备前精确定位的实际作业需求。     

2009 IEEE Congress on Evolutionary Computation (CEC 2009) [Conference Reports]

The 2009 IEEE Congress on Evolutionary Computation (CEC 2009) was held at the Nova Conference Centre and Cinema, Trondheim, Norway during May 18th-21st, 2009. CEC 2009 was the eleventh occurrence of this major event in the evolutionary calendar. It was also the first time IEEE CEC has been held in Scandinavia.     

遗传算法在考虑能耗的单机批调度中的应用

能耗总成本已成为生产调度中一个重要考虑因素,需要在最大完成时间和能耗总成本之间进行权衡,论文将遗传算法（GA）应用到考虑能耗的单机批调度中,并建立同时优化最大化完成时间和最小化能耗总成本的差异工件单机批调度模型.通过遗传算法在考虑能耗（CEC）和不考虑能耗（IEC）下求出非支配解集,利用工件分批的优化和对遗传选择算子的改进,以保证搜索的效率.实验结果表明,与IEC相比,在CEC下使用遗传算法求出的解效果更好,且随着问题规模的增大和工件加工功率的增加,所得解的优势更加明显.     

SoftMC 2003: Workshop on Software Model Checking

This volume contains the Proceedings of the 2^nd Workshop on Software Model Checking, which was held on 14 July 2003 in Boulder, Colorado. The Workshop was a satellite event of the Conference on Computer Aided Verification (CAV) 2003.The first Workshop on Software Model Checking (SoftMC) was held in 2001. Since that time, the field has grown tremendously and we've made a lot of progress in pushing the state-of-the-art. We are now entering a stage where the strengths and limitations of the current approaches are perhaps better understood. With this in mind we invited Dawson Engler to open the workshop with a presentation on using both static analysis and model checking for finding errors in programs. A companion paper to this presentation is included in the proceedings.But, what does the future hold? Can we analyze real programs? Will software model checking ever be push-button? Do we (only) care about finding errors? Can we leverage SAT technology like hardware model checking does? Hopefully we answered some of these questions and more at the 2003 Workshop on Software Model Checking. Our intention for this second workshop was to help provide a springboard for the next phase of development in software model checking.The call for papers resulted in 18 submissions, of which 8 were selected for presentation. The selection process consisted of each paper receiving 3 reviews, followed by a virtual Program Committee meeting. This year the selection process was particularly hard, due to the high level of the submissions, and we are very grateful to the PC and the additional reviewers for their efforts in this regard.Program Committee

Byron Cook (Microsoft)

David Dill (Stanford University)

Patrice Godefroid (Bell Laboratories, Lucent Technologies)

Susanne Graf (Verimag)

Gerard Holzmann (NASA/JPL Laboratory for Reliable Software)

Radu Mateescu (INRIA Rhône-Alpes/VASY)

Scott Stoller (State University of New York at Stony Brook)

Willem Visser (RIACS/NASA Ames Research Center)

Additional Reviewers: Aurore Collomb, Shuvendu Lahiri, Frederic Lang, Jacob Lichtenberg, Kedar Namjoshi and Wendelin SerweWe would also like to thank Microsoft Research for generously providing financial support and the CAV 2003 organizers for their help in organizing the workshop.     

CIPHER EQUIPMENT

Abstract

For a recent student conference, the authors developed a day-long design problem and competition suitable for engineering, mathematics, and science undergraduates. The competition included a cryptography problem, for which a workshop was run during the conference. This paper describes the competition, focusing on the cryptography problem and the workshop. Notes from the workshop and code for the computer programs are made available via the Internet. The results of a personal self-evaluation (PSE) are described.     

Normalized Interactions between autonomous agents

The CEC Project GOAL (Esprit 6283) aims to develop generic software tools to support a new project management paradigm, in which projects are collaborative, decentralised and inter-organizational. To support inter-organizational interaction, communication and cooperation, we are developing a design framework for formalizing the flow of information between organizations, specifying access to and provision of project services, and defining project-wide standards and procedures. This framework is based on normalizing interactions between autonomous software agents by specifying messages and protocols for inter-agent communication and cooperation. This paper reviews the framework, and then focusses on the specification and implementation of a case study, the automation of a distributed document review procedure. This is both a successful proof of concept and a demonstration of how Artificial Intelligence technologies can support inter-organizational project management. It also points the way to agent brokering, an enhancement of object brokering in distributed open systems, where the satisfaction of service requests can be subject to negotiation.Supported by CEC Esprit Project GOAL (Esprit 6283) and CEC Esprit BRA Medlar II (Esprit 6471).Supported by CEC Esprit Project GOAL (Esprit 6283).     

An efficient hybrid technique for numerical optimization and applications

Real World Optimization Problems is one of the major concerns to show the potential and effectiveness of an optimization algorithm. In this context, a hybrid algorithm of two popular heuristics namely Differential Evolution (DE) and Particle Swarm Optimization (PSO) engaged on a ‘tri-population’ environment. Initially, the whole population (in increasing order of fitness) is divided into three groups – Inferior Group, Mid Group and Superior Group. DE is employed in the inferior and superior groups, whereas PSO is used in the mid-group. The proposed method is abbreviated as DPD as it uses DE–PSO–DE on a population. Two strategies namely Elitism (to retain the best obtained values so far) and Non-redundant search (to improve the solution quality) have been additionally employed in DPD cycle. Moreover, the robustness of the mutation strategies of DE have been well studied and suitable mutation strategies for both DEs (for DPD) are investigated over a set of existing 8 popular mutation strategies which results 64 variants of DPD. The top DPD is further tested through the test functions of CEC2006, CEC2010 and 5 Engineering Design Problems. Also it is used to solve CEC2011 Real World Optimization problems. An excellent efficiency of the recommended DPD is confirmed over the state-of-the-art algorithms.     

Cross-entropy clustering

We build a general and easily applicable clustering theory, which we call cross-entropy clustering (shortly CEC), which joins the advantages of classical k-means (easy implementation and speed) with those of EM (affine invariance and ability to adapt to clusters of desired shapes). Moreover, contrary to k-means and EM, CEC finds the optimal number of clusters by automatically removing groups which have negative information cost.     

Introduction to the special issue on normative multiagent systems

This special issue contains four selected and revised papers from the second international workshop on normative multiagent systems, for short NorMAS07 (Boella et al. (eds) Normative multiagent systems. Dagstuhl seminar proceedings 07122, 2007), held at Schloss Dagstuhl, Germany, in March 2007. At the workshop a shift was identified in the research community from a legal to an interactionist view on normative multiagent systems. In this editorial we discuss the shift, examples, and 10 new challenges in this more dynamic setting, which we use to introduce the papers of this special issue.