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Recently, the algorithms for the processing of the visual information have greatly evolved, providing efficient and effective solutions to cope with the variability and the complexity of real-world environments. These achievements yield to the development of Machine Vision systems that overcome the typical industrial applications, where the environments are controlled and the tasks are very specific, towards the use of innovative solutions to face with everyday needs of people. The Human-Centric Machine Vision can help to solve the problems raised by the needs of our society, e.g. security and safety, health care, medical imaging, and human machine interface. In such applications it is necessary to handle changing, unpredictable and complex situations, and to take care of the presence of humans.

Automatic hypothesis formation. --- Mechanized hypothesis formation --- Artificial intelligence --- Hypothesis --- Induction (Mathematics) --- Machine learning

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1 “Change is inevitable.” Embracing this quote we have tried to carefully experiment with the format of this conference, the 15th International Conference on Inductive Logic Programming, hopefully making it even better than it already was. But it will be up to you, the inquisitive reader of this book, to judge our success. The major changes comprised broadening the scope of the conference to include more diverse forms of non-propositional learning, to once again have tutorials on exciting new areas, and, for the ?rst time, to also have a discovery challenge as a platform for collaborative work. This year the conference was co-located with ICML 2005, the 22nd International Conference on Machine Learning, and also in close proximity to IJCAI 2005, the 19th International Joint Conference on Artificial Intelligence. - location can be tricky, but we greatly benefited from the local support provided by Codrina Lauth, Michael May, and others. We were also able to invite all ILP and ICML participants to shared events including a poster session, an invited talk, and a tutorial about the exciting new area of “statistical relational learning”. Two more invited talks were exclusively given to ILP participants and were presented as a kind of stock-taking—fittingly so for the 15th event in a series—but also tried to provide a recipe for future endeavors.

Software engineering. --- Artificial intelligence. --- Computer programming. --- Mathematical logic. --- Algorithms. --- Software Engineering/Programming and Operating Systems. --- Artificial Intelligence. --- Programming Techniques. --- Mathematical Logic and Formal Languages. --- Algorithm Analysis and Problem Complexity. --- Logic programming --- Automatic hypothesis formation

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1 “Change is inevitable.” Embracing this quote we have tried to carefully experiment with the format of this conference, the 15th International Conference on Inductive Logic Programming, hopefully making it even better than it already was. But it will be up to you, the inquisitive reader of this book, to judge our success. The major changes comprised broadening the scope of the conference to include more diverse forms of non-propositional learning, to once again have tutorials on exciting new areas, and, for the ?rst time, to also have a discovery challenge as a platform for collaborative work. This year the conference was co-located with ICML 2005, the 22nd International Conference on Machine Learning, and also in close proximity to IJCAI 2005, the 19th International Joint Conference on Artificial Intelligence. - location can be tricky, but we greatly benefited from the local support provided by Codrina Lauth, Michael May, and others. We were also able to invite all ILP and ICML participants to shared events including a poster session, an invited talk, and a tutorial about the exciting new area of “statistical relational learning”. Two more invited talks were exclusively given to ILP participants and were presented as a kind of stock-taking—fittingly so for the 15th event in a series—but also tried to provide a recipe for future endeavors.

Software engineering. --- Artificial intelligence. --- Computer programming. --- Mathematical logic. --- Algorithms. --- Software Engineering/Programming and Operating Systems. --- Artificial Intelligence. --- Programming Techniques. --- Mathematical Logic and Formal Languages. --- Algorithm Analysis and Problem Complexity. --- Logic programming --- Automatic hypothesis formation

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The inherent dangers of change are often summed up in the misquoted Chinese curse “May you live in interesting times.” The submission procedure for the 16th International Conference of Inductive Logic Programming (ILP 2006) was a radical (hopefully interesting but not cursed) departure from previous years. Submissions were requested in two phases. The ?rst phase involved submission of short papers (three pages) which were then presented at the conference and included in a short papers proceedings. In the second phase, reviewers selected papersforlongpapersubmission(15pagesmaximum).Thesewerethenassessed by the same reviewers, who then decided which papers to include in the journal special issue and proceedings. In the ?rst phase there were a record 77 papers, comparedto the usual20 orso long papersofpreviousyears.Eachpaper was- viewed by three reviewers. Out of these, 71 contributors were invited to submit long papers. Out of the long paper submissions, 7 were selected for the - chine Learning Journal special issue and 27 were accepted for the proceedings. In addition, two papers were nominated by Program Committee referees for the applications prize and two for the theory prize. The papers represent the div- sity and vitality in present ILP research including ILP theory, implementations, search and phase transition, distributed and large-scale learning, probabilistic ILP, biological applications, natural language learning and planning and action learning.

681.3*D16 <063> --- Logic programming --- 681.3*I26 <063> --- 681.3*I25 <063> --- 681.3*I25 <063> Programming languages and software: expert system tools and techniques (Artificial intelligence)--See also {681.3*D32}--Congressen --- Programming languages and software: expert system tools and techniques (Artificial intelligence)--See also {681.3*D32}--Congressen --- 681.3*I26 <063> Learning: analogies concept learning induction knowledge acquisition language acquisition parameter learning (Artificial intelligence)--See also {681.3*K32}--Congressen --- Learning: analogies concept learning induction knowledge acquisition language acquisition parameter learning (Artificial intelligence)--See also {681.3*K32}--Congressen --- Computer programming --- Programming techniques: Logic programming--Congressen --- Conferences - Meetings --- Automatic hypothesis formation --- Génération automatique d'hypothèses --- Computer science. --- Software engineering. --- Computer programming. --- Algorithms. --- Mathematical logic. --- Artificial intelligence. --- Computer Science. --- Software Engineering/Programming and Operating Systems. --- Artificial Intelligence (incl. Robotics). --- Programming Techniques. --- Mathematical Logic and Formal Languages. --- Algorithm Analysis and Problem Complexity. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Algebra of logic --- Logic, Universal --- Mathematical logic --- Symbolic and mathematical logic --- Symbolic logic --- Mathematics --- Algebra, Abstract --- Metamathematics --- Set theory --- Syllogism --- Algorism --- Algebra --- Arithmetic --- Computers --- Electronic computer programming --- Electronic digital computers --- Programming (Electronic computers) --- Coding theory --- Computer software engineering --- Engineering --- Informatics --- Science --- Foundations --- Programming --- 681.3*I26 <063> Learning: analogies; concept learning; induction; knowledge acquisition; language acquisition; parameter learning (Artificial intelligence)--See also {681.3*K32}--Congressen --- Learning: analogies; concept learning; induction; knowledge acquisition; language acquisition; parameter learning (Artificial intelligence)--See also {681.3*K32}--Congressen --- Information Technology --- Artificial Intelligence --- Computer software. --- Artificial Intelligence. --- Software, Computer --- Computer systems