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87 results on '"Vrakas, Dimitris"'

61. AI in Greece: The Case of Research on Linked Geospa al Data

Author

Koubarakis, Manolis, primary, Vouros, George, additional, Chalkiadakis, Georgios, additional, Plagianakos, Vassilis, additional, Tjortjis, Christos, additional, Kavallieratou, Ergina, additional, Vrakas, Dimitris, additional, Mavridis, Nikolaos, additional, Petasis, Georgios, additional, Blekas, Konstantinos, additional, and Krithara, Anastasia, additional

Published
2018
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62. Preface

Author

Bikakis, Antonis, primary, Bassiliades, Nick, additional, and Vrakas, Dimitris, additional

Published
2018
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73. Iridescent

Author

Stavropoulos, Thanos G., primary, Vrakas, Dimitris, additional, and Vlahavas, Ioannis, additional

Published
2013
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75. BOnSAI

Author

Stavropoulos, Thanos G., primary, Vrakas, Dimitris, additional, Vlachava, Danai, additional, and Bassiliades, Nick, additional

Published
2012
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76. IRISPortal

Author

Meditskos, Georgios, primary, Bassiliades, Nick, additional, Vrakas, Dimitris, additional, and Vlahavas, Ioannis, additional

Published
2012
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83. BOnSAI.

Author

Stavropoulos, Thanos G., Vrakas, Dimitris, Vlachava, Danai, and Bassiliades, Nick

Published
2012
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84. IRISPortal.

Author

Meditskos, Georgios, Bassiliades, Nick, Vrakas, Dimitris, and Vlahavas, Ioannis

Published
2012
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85. Towards Automatic Synthesis of Educational Resources Through Automated Planning.

Author

Antoniou, Grigoris, Potamias, George, Spyropoulos, Costas, Plexousakis, Dimitris, Vrakas, Dimitris, Kokkoras, Fotis, Bassiliades, Nick, and Vlahavas, Ioannis

Abstract

This paper reports on the results of an ongoing project for the development of a platform for e-Learning, which automatically constructs curricula based on available educational resources and the learners needs and abilities. The system under development, called PASER (Planner for the Automatic Synthesis of Educational Resources), uses an automated planner, which given the initial state of the problem (learner's profile, preferences, needs and abilities), the available actions (study an educational resource, take an exam, join an e-learning course, etc.) and the goals (obtain a certificate, learn a subject, acquire a skill, etc.) constructs a complete educational curriculum that achieves the goals. PASER is compliant with the evolving educational metadata standards that describe learning resources (LOM), content packaging (CP), educational objectives (RDCEO) and learner related information (LIP). [ABSTRACT FROM AUTHOR]

Published
2006
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87. HAPRC: an automatically configurable planning system.

Author

Vrakas, Dimitris, Tsoumakas, Grigorios, Bassiliades, Nick, and Vlahavas, Ioannis

Subjects
*PLANNING, *MACHINE learning, *MACHINE theory, *ALGORITHMS, *PARAMETER estimation
Abstract

This paper presents an adaptive planning system, called HAPRC, which automatically fine-tunes its planning parameters according to the morphology of the problem in hand, through a combination of Planning, Machine Learning and Knowledge-Based techniques. The adaptation is guided by a rule-based system that sets planner configuration parameters based on measurable characteristics of the problem instance. The knowledge of the rule system has been acquired through a rule induction algorithm. Specifically, the approach of propositional rule learning was applied to a dataset produced by results from experiments on a large number of problems from various domains, including those used in the three International Planning Competitions. The improvement of the adaptive system over the original planner is assessed through thorough experiments in problems of both known and unknown domains. [ABSTRACT FROM AUTHOR]

Published
2005

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