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Intelligent Systems, IEEE

Issue 4 • Date July-Aug. 2007

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Displaying Results 1 - 17 of 17
  • [Front cover]

    Publication Year: 2007 , Page(s): c1
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  • Table of contents

    Publication Year: 2007 , Page(s): c2
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  • Agents Redux

    Publication Year: 2007 , Page(s): 2
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  • The Challenge of Finding Intelligent Agents

    Publication Year: 2007 , Page(s): 3 - 5, 7
    Cited by:  Papers (3)
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  • The Agents Are All Busy Doing Stuff!

    Publication Year: 2007 , Page(s): 6 - 7
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (68 KB) |  | HTML iconHTML  

    In answer to the question, "Where have all the agents gone?" this column asserts that agent technologies are pervasive, not missing. View full abstract»

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  • In the News

    Publication Year: 2007 , Page(s): 8 - 11
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  • Mexar2: AI Solves Mission Planner Problems

    Publication Year: 2007 , Page(s): 12 - 19
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1349 KB) |  | HTML iconHTML  

    Deep-space missions carry an ever larger set of different and complementary onboard payloads. Each payload generates data, and synthesizing it for optimized downlinking is one way to reduce the ratio of mission costs to science return. This is the main role of the Mars-Express scheduling architecture (Mexar2), an Al-based tool in daily use on the Mars-Express mission since February 2005. Mexar2 supports space mission planners continuously as they plan data downlinks from the spacecraft to Earth. The tool lets planners work at a higher abstraction level while it performs low-level, often-repetitive tasks. It also helps them produce a plan rapidly, explore alternative solutions, and choose the most robust plan for execution. Additionally, planners can analyze any problems over multiple days and identify payload overcommitments that cause resource bottlenecks and increase the risk of data losses. Mexar2 has significantly increased the data return over the whole Mars-Express mission duration. It's effectively become a work companion for mission planners at the European Space Agency's European Space Operations Center (ESOC) in Darmstadt, Germany. View full abstract»

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  • Guest Editors' Introduction: Intelligent Educational Systems of the Present and Future

    Publication Year: 2007 , Page(s): 20 - 21
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  • Inducing High-Level Behaviors from Problem-Solving Traces Using Machine-Learning Tools

    Publication Year: 2007 , Page(s): 22 - 30
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (706 KB) |  | HTML iconHTML  

    Many researchers consider interactive learning environments to be interesting solutions for overcoming the limits of classical one-to-many teaching methods. However, these environments should incorporate accurate representations of student knowledge to provide relevant guidance. In a problem-solving environment, one way to build and update this student model is model tracing, or using a detailed representation of cognitive skills to precisely follow what the student is doing. Some model-tracing tutors such as PAT (Personal Algebra Tutor) contain rules that the system can use to solve the problem and assess the student's solution. View full abstract»

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  • Adaptive Hypermedia Techniques for 3D Educational Virtual Environments

    Publication Year: 2007 , Page(s): 31 - 37
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (757 KB) |  | HTML iconHTML  

    Based on a well-known adaptive hypermedia framework, the proposed system creates a 3D educational virtual environment that selects and personalizes interactive learning content for users. In EVEs, users not only see concepts visualized, but they can perform tasks in a suitable fictional world or a real-world reproduction. Moreover, compared to 2D multimedia, using interactive 3D graphics lets developers create representations of subjects or phenomena that are more informative and make it possible for users to analyze a single subject from different viewpoints. In EVEs, adaptivity can play an important role in increasing both learning-process effectiveness and interface usability. View full abstract»

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  • Intelligent Tutors for All: The Constraint-Based Approach

    Publication Year: 2007 , Page(s): 38 - 45
    Cited by:  Papers (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (489 KB) |  | HTML iconHTML  

    This paper presents a new type of intelligent tutoring systems, called constraint-based tutors. The system have been thoroughly evaluated and proven to achieve significant learning gains. View full abstract»

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  • Improving Student Performance Using Self-Assessment Tests

    Publication Year: 2007 , Page(s): 46 - 52
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (200 KB) |  | HTML iconHTML  

    Testing is the most generic and perhaps most widely used mechanism for student assessment. Most tests are based on the classical test theory, which says that a student's score is the sum of the scores obtained in all questions plus some kind of error. The most relevant is that the student test result depends heavily on the individual's learning preferences or abilities and also on the actual test's format. According to this theory, tests aren't necessarily useful in intelligent educational systems, which require accurately obtaining the student's knowledge state to guide the learning process. Yet the Web has created a new generation of intelligent systems-adaptive hypermedia systems which offer new types of instructional interaction. Educational AHSs adapt the learning process on the basis of the student's learning preferences, knowledge, and availability. One such Web-based tool is Siette (the system of intelligent evaluation using rests), which infers student knowledge using adaptive testing. View full abstract»

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  • Toward an Affect-Sensitive AutoTutor

    Publication Year: 2007 , Page(s): 53 - 61
    Cited by:  Papers (41)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (752 KB) |  | HTML iconHTML  

    Here, we consider the possibility of enabling AutoTutor, an intelligent tutoring system, to process learners' affective and cognitive states. AutoTutor is a fully automated computer tutor that simulates human tutors and converses with students in natural language. View full abstract»

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  • Gender-Specific Approaches to Developing Emotionally Intelligent Learning Companions

    Publication Year: 2007 , Page(s): 62 - 69
    Cited by:  Papers (18)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (386 KB) |  | HTML iconHTML  

    The nonverbal social behaviors of virtual learning companions and their affect and task support have gender-specific impacts on learners' frustration and self-awareness during a challenging problem-solving activity. Social bonding and affective support between teachers and learners have considerable impact on learners' performance and motivation. One way to develop a social bond with learners is to provide assistance. According to research in this area (see the sidebar "Related Work on Affective Tutoring Systems"), systems that provide affective support to frustrated users can reduce frustration. A study of expert human tutors' interactions with their students found that up to half of these interactions focus on supporting the learner's affective state. Currently, most intelligent tutoring systems provide predominantly task-based support. View full abstract»

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  • COMET: A Collaborative Tutoring System for Medical Problem-Based Learning

    Publication Year: 2007 , Page(s): 70 - 77
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1456 KB) |  | HTML iconHTML  

    This paper discussed about the developed collaborative intelligent tutoring system for medical PBL called Comet (collaborative medical tutor). Comet uses Bayesian networks to model the knowledge and activity of individual students as well as small groups. It applies generic tutoring algorithms to these models and generates tutorial hints that guide problem solving. An early laboratory study shows a high degree of agreement between the hints generated by Comet and those of experienced human tutors. Evaluations of Comet's clinical-reasoning model and the group reasoning path provide encouraging support for the general framework. View full abstract»

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  • Domain-Driven, Actionable Knowledge Discovery

    Publication Year: 2007 , Page(s): 78 - 88, c3
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (478 KB) |  | HTML iconHTML  

    Data mining increasingly faces complex challenges in the real-life world of business problems and needs. The gap between business expectations and R&D results in this area involves key aspects of the field, such as methodologies, targeted problems, pattern interestingness, and infrastructure support. Both researchers and practitioners are realizing the importance of domain knowledge to close this gap and develop actionable knowledge for real user needs. View full abstract»

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  • [Back cover]

    Publication Year: 2007 , Page(s): c4
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Aims & Scope

IEEE Intelligent Systems serves users, managers, developers, researchers, and purchasers who are interested in intelligent systems and artificial intelligence, with particular emphasis on applications.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Daniel Zeng
University of Arizona