339 search hits
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William Carlos Williams review : WCWR
(2012)
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Proceedings of the ACM SIGPLAN Workshop on Approaches and Applications of Inductive Programming (AAIP 2009)
(2009)
- Inductive programming is concerned with the automated construction of declarative, often functional, recursive programs from incomplete specifications such as input/output examples. The inferred program must be correct with respect to the provided examples in a generalising sense: it should be neither equivalent to them, nor inconsistent. Inductive programming algorithms are guided explicitly or implicitly by a language bias (the class of programs that can be induced) and a search bias (determining which generalised program is constructed first). Induction strategies are either generate-and-test or example-driven. In generate-and-test approaches, hypotheses about candidate programs are generated independently from the given specifications. Program candidates are tested against the given specification and one or more of the best evaluated candidates are developed further. In analytical approaches, candidate programs are constructed in an example-driven way. While generate-and-test approaches can -- in principle -- construct any kind of program, analytical approaches have a more limited scope. On the other hand, efficiency of induction is much higher in analytical approaches. Inductive programming is still mainly a topic of basic research, exploring how the intellectual ability of humans to infer generalised recursive procedures from incomplete evidence can be captured in the form of synthesis methods. Intended applications are mainly in the domain of programming assistance -- either to relieve professional programmers from routine tasks or to enable non-programmers to some limited form of end-user programming. Furthermore, in the future, inductive programming techniques might be applied to further areas such as supporting the inference of lemmata in theorem proving or learning grammar rules. Inductive automated program construction has been originally addressed by researchers in artificial intelligence and machine learning. During the last years, some work on exploiting induction techniques has been started also in the functional programming community. Therefore, the third workshop on |Approaches and Applications of Inductive Programming| took place for the first time in conjunction with the ACM SIGPLAN International Conference on Functional Programming (ICFP 2009). The first and second workshop were associated with the International Conference on Machine Learning (ICML 2005) and the European Conference on Machine Learning (ECML 2007). AAIP´09 aimed to bring together researchers from the functional programming and the artificial intelligence communities, working in the field of inductive functional programming, and advance fruitful interactions between these communities with respect to programming techniques for inductive programming algorithms, the identification of challenge problems and potential applications. For everybody interested in inductive programming we recommend to visit the website: www.inductive-programming.org.
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Proceedings of the KI 2009 Workshop on Complex Cognition
(2009)
- The KI ´09 workshop on Complex Cognition was a joint venture of the Cognition group of the Special Interest Group Artificial Intelligence of the German Computer Science Society (Gesellschaft für Informatik) and the German Cognitive Science Association. Dealing with complexity has become one of the great challenges for modern information societies. To reason and decide, plan and act in complex domains is no longer limited to highly specialized professionals in restricted areas such as medical diagnosis, controlling technical processes, or serious game playing. Complexity has reached everyday life and affects people in such mundane activities as buying a train ticket, investing money, or connecting a home desktop to the internet. Research in cognitive AI can contribute to supporting people navigating through the jungle of everyday reasoning, decision making, planning and acting by providing intelligent support technology. Lessons learned from expert systems research of the nineteen-eighties show that the aim should not be to provide for fully automated systems which can solve specialized tasks autonomously but instead to develop interactive assistant systems where user and system work together by taking advantage of the respective strengths of human and machine. To accomplish a smooth collaboration between humans and intelligent systems, basic research in cognition is a necessary precondition. Insights into cognitive structures and processes underlying successful human reasoning and planning can provide suggestions for algorithm design. Even more important, insights into restrictions and typical errors and misconceptions of the cognitive systems provide information about those parts of a complex task from which the human should be relieved. For successful human-computer interaction in complex domains it has, furthermore, to be decided which information should be presented when, in what way, to the user. We strongly believe that symbolic approaches of AI and psychological research of higher cognition are at the core of success for the endeavor to create intelligent assistant system for complex domains. While insight into the neurological processes of the brain and into the realization of basic processes of perception, attention and senso-motoric coordination are important for the basic understanding of the principles of human intelligence, these processes have a much too fine granularity for the design and realization of interactive systems which must communicate with the user on knowledge level. If human system users are not to be incapacitated by a system, system decisions must be transparent for the user and the system must be able to provide explanations for the reasons of its proposals and recommendations. Therefore, even when some of the underlying algorithms are based on statistical or neuronal approaches, the top-level of such systems must be symbolical and rule-based. The papers presented at this workshop on complex cognition give an inspiring and promising overview of current work in the field which can provide first building stones for our endeavor to create knowledge level intelligent assistant systems for complex domains. The topics cover modelling basic cognitive processes, interfacing subsymbolic and symbolic representations, dealing with continuous time, Bayesian identification of problem solving strategies, linguistically inspired methods for assessing complex cognitive processes and complex domains such as recognition of sketches, predicting changes in stocks, spatial information processing, and coping with critical situations.
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English past and present : selected papers from the IAUPE Malta Conference in 2010
(2012)
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A statistical equilibrium model of competitive firms
(2012)
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Simone Alfarano
Mishael Milakovic
Albrecht Irle
Jonas Kauschke
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Liturgy of the Hours and Islamic Salat - A comparative study of public-liturgical worship of Christians and Muslims
(2002)
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Alfred C. Anazodo
- This work aims to explore the possibilities of multireligious encounter of Muslims and Christians, in view of the liturgical worship, a problem which is highly controversial. It studies the ritual acts of the Muslims and Christians in the celebration of the daily worship as an expression of their belief in God's presence, mercy and goodness as outlined by Vatican Council II (Nostra aetate 3).
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Home and preschool learning environments and their relations to the development of early numeracy skills
(2012)
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Yvonne Anders
Hans-Günther Roßbach
Sabine Weinert
Susanne Ebert
Susanne Kuger
Simone Lehrl
Jutta von Maurice
- This study examined the influence of the quality of home and preschool learning environments on the
development of early numeracy skills in Germany, drawing on a sample of 532 children in 97 preschools.
Latent growth curve models were used to investigate early numeracy skills and their development from
the first (average age: 3 years) to the third year (average age: 5 years) of preschool. Several child and family
background factors (e.g., gender, maternal education, socioeconomic status), measures of the home
learning environment (e.g., literacy- and numeracy-related activities), and measures of preschool structural
and process quality (e.g., ECERS-E, ECERS-R) were tested as predictors of numeracy skills and their
development. The analyses identified child and family background factors that predicted numeracy skills
in the first year of preschool and their development over the three points of measurement — particularly
gender, parental native language status (German/other), socioeconomic status, and mother’s educational
level. The quality of the home learning environment was strongly associated with numeracy skills in the
first year of preschool, and this advantage was maintained at later ages. In contrast, the process quality of
the preschool was not related to numeracy skills at the first measurement, but was significantly related to
development over the period observed. The results underline the differential impact of the two learning
environments on the development of numeracy skills. Interaction effects are explored and discussed.
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Introduction : Self-Initiated Expatriation: Individual, Organizational, and National Perspectives
(2012)
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Maike Andresen
Akram Al Ariss
Matthias Walther
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Self-Initiated Expatriation: Individual, Organizational, and National Perspectives
(2012)
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Maike Andresen
Akram Al Ariss
Matthias Walther
Franziska Bergdolt
Thomas Egner
Jil Margenfeld
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Vance, Charles M., Managing a Global Workforce : Challenges and Opportunities in International Human Resource Management / Charles M. Vance and Yongsun Paik. - 2. ed. : Armonk, NY [u.a.], 2011
(2012)
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Maike Andresen
Franziska Bergdolt