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Intelligent Agent Technology, 2007. IAT '07. IEEE/WIC/ACM International Conference on

Date 2-5 Nov. 2007

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Displaying Results 1 - 25 of 108
  • 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology - Cover

    Page(s): c1
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  • 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology - Title page

    Page(s): i - iii
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  • 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology - Copyright

    Page(s): iv
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  • 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology - TOC

    Page(s): v - xi
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  • Welcome Message from the Conference Chair and Program Chair

    Page(s): xii - xiv
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  • Conference organization

    Page(s): xv - xvi
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  • Program Committee Members

    Page(s): xvii - xviii
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  • Reviewers

    Page(s): xix
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  • WI'07/IAT'07/BIBM'07/GrC'07 Joint Keynote: Computer Science as a Lens on the Sciences: The Example of Computational Molecular Biology

    Page(s): xxi
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (245 KB) |  | HTML iconHTML  

    This talk will trace the growing influence of fundamental ideas from computer science on the nature of research in a number of scientific fields. There is a growing awareness that information processing lies at the heart of the processes studied in fields as diverse as quantum mechanics, statistical physics, nanotechnology, neuroscience, linguistics, economics and sociology. Increasingly, mathematical models in these fields are expressed in algorithmic languages and describe algorithmic processes. The speaker will briefly describe connections between quantum computing and the foundations of quantum mechanics, and between statistical mechanics and phase transitions in computation. He will indicate how the growth of the Web has created new phenomena to be investigated by sociologists and economists. He will then focus in greater detail on computational molecular biology, where the view of living cells as complex information processing systems has become the dominant paradigm, and will discuss specific algorithmic problems arising in the sequencing of genomes, the comparative analysis of the resulting genomic sequences,the modeling of networks of interacting proteins, and the associations between genetic variation and disease. View full abstract»

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  • ServiceWeb 3.0

    Page(s): xxii
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    Computer science is entering a new generation. The previous generation was based on abstracting from hardware. The emerging generation comes from abstracting from software and sees all resources as services in a service-oriented architecture (SOA). In a world of services, it is the service that counts for a customer and not the software or hardware components that implement the service. Service-oriented architectures are rapidly becoming the dominant computing paradigm. However, current SOA solutions are still restricted in their application context to in-house solution of companies. A service web will have billions of services. While service orientation is widely acknowledged for its potential to revolutionize the world of computing by abstracting form underlying hardware and software layers, that success depends on resolving fundamental challenges that SOA does not address currently. The mission of Service Web 3.0 is to provide solutions to integration and search that will enable the Service Oriented Architecture (SOA) revolution on a worldwide scale. Hereby we must focus on three major areas where we need to extend current approaches towards service orientation: Web technology as an infrastructure and underlying infrastructure for integration of services at a world wide scale. SemanticWeb technology as a means to abstract from syntax to semantics; and Web 2.0 as a means to structure human-machine cooperation in an efficient and costeffective manner Service Web 3.0 will place computing and programming at the services layer providing the real goal of computing: problem solving in the hands of end users through a properly balanced cooperation approach. Humans are much better in solving certain tasks (capture recognition, image descriptions, common sense reasoning, f.e., http://video.google.com/videoplay?docid=-8246463980976635143&hl=en). View full abstract»

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  • Conversational Informatics and Human-CenteredWeb Intelligence

    Page(s): xxiii
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    Conversation is the most natural communication means for people to communicate with each other. I believe that conversation plays a critical role in realizing a paradigm of human-centered web intelligence in which web intelligence engines are grounded on the human society. We are currently building a computational framework for circulating information in a conversational fashion, using information packages called conversation quanta that encapsulate conversational scenes. Technologies are being developed for acquiring conversation quanta on the spot, accumulating them in a visually recognizable form, and reusing them in a situated fashion. Conversational Informatics constitutes the theoretical foundation for measurement, analysis, and modeling of conversation. I will overview recent results in Conversational Informatics that will help achieve our vision. I will also discuss our approach in the context of Social Intelligence Design aimed at the understanding and augmentation of social intelligence for collective problem solving and learning. View full abstract»

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  • How Relevant is Game Theory to Intelligent Agent Technology?

    Page(s): xxiv
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    At this point, restricted to rather specialized areas, and even there must be taken with a grain of salt. But at the same time you can't afford not to know it; there is currently no better underpinning for understanding multiagent systems. I will elaborate using experience in both academia and industry. View full abstract»

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  • The Challenge of Cultural Modeling for Inferring Intentions and Behavior

    Page(s): xxv
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    Accounting for social, cultural, and political factors must form the basis for understanding decision-making, actions, and reactions of individuals, thus driving their behaviors and intentions. Clearly, the individual is not wholly defined by just personal social, cultural, and political beliefs but also functions within a group of individuals. Within these groups (or organizations), they assimilate a potentially wide variety of different social factors, which may or may not differ from their own. Also, the group itself can vary in degrees of complexity, styles of interaction, and so forth, resulting in highly dynamic and emergent modes of behaviors. Even more difficult, this also includes taking into account the values, attitudes, and beliefs of the local population/environment that the individual/group is situated within. Without all these factors, we cannot expect to effectively understand, analyze, or predict the behaviors and intentions of others which grows ever more critical as our society continues to globalize and especially in today's conflicts and catastrophes. Thus, the need for a comprehensive modeling framework is evident as our only real hope of addressing such complexity. However, to date, only small isolated groups of pertinent behavioral factors have been studied, while there is little or no work towards developing a general unified and comprehensive approach that is also computational. The major challenges we face can be summed up in the following questions: 1. For prediction and explanation of intent and behavior, how does one computationally model individual or organizations and their emergent interactions with others, in various situations? 2. How does one organize and build the necessary social, cultural, political, behavioral, etc. knowledge- base? 3. How do you avoid brittleness and overspecialization? How do you construct these models efficiently and effectively, and dynamically evolve such models over time based on changing cultural and s- ocial factors? 4. How do you validate your models? In this talk, we will explore these challenges and focus on addressing pragmatic and computational issues in such modeling and examine some existing real-world efforts, current solutions, and openquestions. View full abstract»

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  • Granular Computing forWeb Intelligence and Brain Informatics

    Page(s): xxvi - xxix
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    In this talk, we examine the basic principles, ideas, and strategies of granular computing, and look at the potential applications and implications of granular computing to the studies of Web Intelligence (WI) and Brain Informatics (BI).We argue that granular computing may provide the necessary theory for designing and implementing new types of web-based information processing systems and developing a conceptual model of the human brain. View full abstract»

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  • Revisiting ADOPT-ing and its Feedback Schemes

    Page(s): 3 - 9
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    Here we revisit ADOPT-ing and bring two new contributions. One contribution consists of developing variations on the algorithms keeping the improvement in length of chain of causal messages without an increase in the total number of messages. While past experiments have shown that sending more feedback is better than sending the minimal information needed for correctness, new experiments show that one should not exaggerate sending too much feedback and that the best strategy is at an intermediary point. This brings large efficiency improvements. We also find that one of the no good storages of ADOPT- ing can be removed without effects on efficiency while decreasing the space complexity by a factor given by the number of agents. We also provide a more general proof showing which types of nogood storages can be used in the inference of feedback without compromising correctness. In particular we show that all such structures can be updated by sum-inference, and from threshold messages. View full abstract»

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  • An Ant Colony Optimization Algorithm for Solving the Multidimensional Knapsack Problems

    Page(s): 10 - 16
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    Ant colony optimization (ACO) algorithm is a metaheuristic and stochastic search technology, which has been one of the effective tools for solving discrete optimization problems. However, there are two bottlenecks for large-scaled optimization problems: the ACO algorithm needs too much time to convergent and the solutions may not be really optimal. This paper proposes a novel ACO algorithm for the multidimensional knapsack problems (MKP), which employs a new pheromone diffusion model and a mutation scheme. First, in light of the preference to better solutions, the association distances among objects are mined in each iteration with top-k strategy. Then, a pheromone diffusion model based on info fountain of an object is established, which strengthens the collaborations among ants. Finally, an unique mutation scheme is applied to optimizing the evolution results of each step. The experimental results for the benchmark testing set of MKPs show that the proposed algorithm can not only get much more optimal solutions but also greatly enhance convergence speed. View full abstract»

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  • Dynamic Area Coverage using Faulty Multi-Agent Swarms

    Page(s): 17 - 23
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    We consider the problem of distributed coverage of an unknown two-dimensional environment using a swarm of mobile mini-robots. In contrast to previous approaches for robotic area coverage, we assume that each robot (agent) in our system is limited in its communication range and memory capacity. Agents are also susceptible to sensor noise while communicating with other agents, and, can be subject to transient or permanent failures. The objective of the agents is to cover the entire environment while reducing the coverage time and the redundancy in the area covered by different agents. First, we describe our distributed coverage algorithm where each agent uses a local heuristic based on Manhattan distances and the information gained from other agents at each step to decide on its next action (movement). We then describe and analyze the fault model of our agents and show that the local heuristic used by the agents deteriorate linearly as the communication noise increases. Finally, we verify the performance of our system empirically within a simulated environment and show that the system is able to scale efficiently in the number of robots and size of the environment, and, determine the effect of communication faults and robot failures on the system performance. View full abstract»

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  • Intelligent Agent Technology: An Application to US Wholesale Power Trading

    Page(s): 27 - 30
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    Intelligent agents are gaining widespread applications in many trading markets. Although the US wholesale power market comprises a large commodity market, the mechanism of power trading is not clearly investigated. We explore the problem via an intelligent agent-based approach. We create an artificial wholesale market, where many different traders are equipped with learning capabilities. We validate the agent based model with the help of a data set from PJM electricity market. Using the new intelligence system, we investigate the bidding strategies of traders and examine how the price changes occur under different environments. View full abstract»

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  • Agent-based Fault Detection Mechanism in Wireless Sensor Networks

    Page(s): 31 - 34
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    Recently, agent-based approaches are considered as an appropriate solution to address the issue of the overwhelming data traffic in wireless sensor networks (WSNs). Theoretically, these approaches would eliminate the redundancy and achieve substantial energy gain. However, in practice, the reliability of sensor devices has been recognized as one of the crucial issues in wireless sensor networks. Using agents at the sensor devices may provide more efficient energy consumption. But, micro-sensors are subject to high-frequency faults in distributed environments. Towards this end, we propose agent-based system architecture with fault-detection inference engine based on reverse multicast tree to evaluate sensor nodes' fault probabilities. Due to the characteristics of wireless sensor networks (energy awareness, constraint bandwidth and so on); it is infeasible to require each sensor to announce its working state to a centralized terminal node. Therefore, we formulate the agent's inference engine as nondeterministic finite accepter and adopt iterative computation to infer the fault probability of nodes in reverse multicast tree. View full abstract»

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  • Roller: the Effect of the Environment to the Emergence of Behavior

    Page(s): 35 - 38
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    In this paper, we study the effect of an open environment to the behavior of an autonomous mobile agent. The focus of our study is in the emergent behavior. For this purpose, we use a particle system. With it, we can capture and simulate both the agent and its environment uniformly, to reveal the emergent properties. We illustrate the use of a particle system in analyzing the emergent behavior of a simple moving agent, Roller, in order to improve its performance in an undetermined terrain. View full abstract»

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  • Autonomy with Regard to an Attribute

    Page(s): 39 - 42
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    This paper presents a model of autonomy called autonomy with regard to an attribute applicable to cognitive and not cognitive artificial agents. Three criteria (global /partial, social / nonsocial, absolute / relative) are defined and used to describe the main characteristics of this type of autonomy. View full abstract»

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  • Intelligent Software Agent Design Tool Using Goal Net Methodology

    Page(s): 43 - 46
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (469 KB) |  | HTML iconHTML  

    Intelligent agent is a fast emerging technology and has wide range of applications. Although there are several tools for agent development, there is few design tool to assist the conversion from paper based agent mental state design to effective representation of them in abstract data structures which can be used by the agent management system to create intelligent software agents. This paper proposes the goal net designer which is an integrated development environment (IDE) for modeling agent behavior based on goal net model, a goal orient methodology. It provides a way for the users to simplify the various stages of the design process and automatically generate design data which can be used by the multi- agent development environment (MADE) to automatically create intelligent agents. The system reduces the level of skills required for developing agent augmented application to such an extent that users with little knowledge in intelligent software agent technology can easily add intelligent agents into their applications and save time and cost involved in the development process. View full abstract»

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  • Gastro-Intestinal Tract Inspired Computational Paradigm

    Page(s): 47 - 50
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    The dynamic nature of handling undesirable, irritant and toxic items during digestion process by the defense mechanism associated with the human gastrointestinal tract helps avoid intake of hazardous material in the body. The defense mechanism acts in coordination with the sensory organs and nervous system to keep a human healthy. In this paper, we have mapped the defense mechanism associated with the human gastrointestinal tract from the biological/nature domain to the computer science/information technology domain for proposing a gastrointestinal tract inspired computing model. The proposed model has its roots purely in the biological domain with the softbots used as the main building block for processing. The processing is facilitated by a centralized learning center that mimics the human nervous system functionality. View full abstract»

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  • About Some Specificities of Embedded Multiagent Systems Design

    Page(s): 51 - 54
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    Multiagent systems (MAS) satisfy to design requirements for open physical complex systems. However, up to now, no method allows to build software/hardware hybrid multi- agent systems : we introduce the DIAMOND method. View full abstract»

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  • A Self-Organization Process for Communication Management in Embedded Multiagent Systems

    Page(s): 55 - 58
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    This paper deals with a multiagent self-organization process aiming to give adaptive features to distributed embedded systems involving intelligent agents in open real world. We propose a formal description of this model of self-organization. View full abstract»

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