50 research outputs found
V Jornadas de InvestigaciĂłn de la Facultad de Ciencia y TecnologĂa. 2016
171 p.I. Abstracts. Ahozko komunikazioak / Comunicaciones orales:
1. Biozientziak: Alderdi Molekularrak / Biociencias: Aspectos moleculares.
2. Biozientziak: Ingurune Alderdiak / Biociencias: Aspectos Ambientales.
3. Fisika eta Ingenieritza Elektronika / FĂsica e IngenierĂa ElectrĂłnica.
4. GeologĂa / GeologĂa.
5. Matematika / Matemáticas.
6. Kimika / QuĂmica.
7. Ingenieritza Kimikoa eta Kimika / IngenierĂa QuĂmica y QuĂmica.
II. Abstracts. Idatzizko Komunikazioak (Posterrak) / Comunicaciones escritas (PĂłsters):
1. Biozientziak / Biociencias.
2. Fisika eta Ingenieritza Elektronika / FĂsica e IngenierĂa ElectrĂłnica.
3. Geologia / Geologia.
4. Matematika / Matemáticas.
5. Kimika / QuĂmica.
6. Ingenieritza Kimikoa / IngenierĂa QuĂmica
Recommended from our members
Laboratory Directed Research and Development Program FY 2004 Annual Report
The Oak Ridge National Laboratory (ORNL) Laboratory Directed Research and Development (LDRD) Program reports its status to the U.S. Department of Energy (DOE) in March of each year. The program operates under the authority of DOE Order 413.2A, 'Laboratory Directed Research and Development' (January 8, 2001), which establishes DOE's requirements for the program while providing the Laboratory Director broad flexibility for program implementation. LDRD funds are obtained through a charge to all Laboratory programs. This report describes all ORNL LDRD research activities supported during FY 2004 and includes final reports for completed projects and shorter progress reports for projects that were active, but not completed, during this period. The FY 2004 ORNL LDRD Self-Assessment (ORNL/PPA-2005/2) provides financial data about the FY 2004 projects and an internal evaluation of the program's management process. ORNL is a DOE multiprogram science, technology, and energy laboratory with distinctive capabilities in materials science and engineering, neutron science and technology, energy production and end-use technologies, biological and environmental science, and scientific computing. With these capabilities ORNL conducts basic and applied research and development (R&D) to support DOE's overarching national security mission, which encompasses science, energy resources, environmental quality, and national nuclear security. As a national resource, the Laboratory also applies its capabilities and skills to the specific needs of other federal agencies and customers through the DOE Work For Others (WFO) program. Information about the Laboratory and its programs is available on the Internet at <http://www.ornl.gov/>. LDRD is a relatively small but vital DOE program that allows ORNL, as well as other multiprogram DOE laboratories, to select a limited number of R&D projects for the purpose of: (1) maintaining the scientific and technical vitality of the Laboratory; (2) enhancing the Laboratory's ability to address future DOE missions; (3) fostering creativity and stimulating exploration of forefront science and technology; (4) serving as a proving ground for new research; and (5) supporting high-risk, potentially high-value R&D. Through LDRD the Laboratory is able to improve its distinctive capabilities and enhance its ability to conduct cutting-edge R&D for its DOE and WFO sponsors. To meet the LDRD objectives and fulfill the particular needs of the Laboratory, ORNL has established a program with two components: the Director's R&D Fund and the Seed Money Fund. As outlined in Table 1, these two funds are complementary. The Director's R&D Fund develops new capabilities in support of the Laboratory initiatives, while the Seed Money Fund is open to all innovative ideas that have the potential for enhancing the Laboratory's core scientific and technical competencies. Provision for multiple routes of access to ORNL LDRD funds maximizes the likelihood that novel and seminal ideas with scientific and technological merit will be recognized and supported
Artificial general intelligence: Proceedings of the Second Conference on Artificial General Intelligence, AGI 2009, Arlington, Virginia, USA, March 6-9, 2009
Artificial General Intelligence (AGI) research focuses on the original and ultimate goal of AI – to create broad human-like and transhuman intelligence, by exploring all available paths, including theoretical and experimental computer science, cognitive science, neuroscience, and innovative interdisciplinary methodologies. Due to the difficulty of this task, for the last few decades the majority of AI researchers have focused on what has been called narrow AI – the production of AI systems displaying intelligence regarding specific, highly constrained tasks. In
recent years, however, more and more researchers have recognized the necessity – and feasibility – of returning to the original goals of the field. Increasingly, there is a call for a transition back to confronting the more difficult issues of human level intelligence and more broadly artificial general intelligence
V Jornadas de InvestigaciĂłn de la Facultad de Ciencia y TecnologĂa. 2016
171 p.I. Abstracts. Ahozko komunikazioak / Comunicaciones orales:
1. Biozientziak: Alderdi Molekularrak / Biociencias: Aspectos moleculares.
2. Biozientziak: Ingurune Alderdiak / Biociencias: Aspectos Ambientales.
3. Fisika eta Ingenieritza Elektronika / FĂsica e IngenierĂa ElectrĂłnica.
4. GeologĂa / GeologĂa.
5. Matematika / Matemáticas.
6. Kimika / QuĂmica.
7. Ingenieritza Kimikoa eta Kimika / IngenierĂa QuĂmica y QuĂmica.
II. Abstracts. Idatzizko Komunikazioak (Posterrak) / Comunicaciones escritas (PĂłsters):
1. Biozientziak / Biociencias.
2. Fisika eta Ingenieritza Elektronika / FĂsica e IngenierĂa ElectrĂłnica.
3. Geologia / Geologia.
4. Matematika / Matemáticas.
5. Kimika / QuĂmica.
6. Ingenieritza Kimikoa / IngenierĂa QuĂmica
2017 EURÄ“CA Abstract Book
Listing of student participant abstracts
White Paper 11: Artificial intelligence, robotics & data science
198 p. : 17 cmSIC white paper on Artificial Intelligence, Robotics and Data Science sketches a preliminary roadmap for addressing current R&D challenges associated with automated and autonomous machines. More than 50 research challenges investigated all over Spain by more than 150 experts within CSIC are presented in eight chapters. Chapter One introduces key concepts and tackles the issue of the integration of knowledge (representation), reasoning and learning in the design of artificial entities. Chapter Two analyses challenges associated with the development of theories –and supporting technologies– for modelling the behaviour of autonomous agents. Specifically, it pays attention to the interplay between elements at micro level (individual autonomous agent interactions) with the macro world (the properties we seek in large and complex societies). While Chapter Three discusses the variety of data science applications currently used in all fields of science, paying particular attention to Machine Learning (ML) techniques, Chapter Four presents current development in various areas of robotics. Chapter Five explores the challenges associated with computational cognitive models. Chapter Six pays attention to the ethical, legal, economic and social challenges coming alongside the development of smart systems. Chapter Seven engages with the problem of the environmental sustainability of deploying intelligent systems at large scale. Finally, Chapter Eight deals with the complexity of ensuring the security, safety, resilience and privacy-protection of smart systems against cyber threats.18 EXECUTIVE SUMMARY ARTIFICIAL INTELLIGENCE, ROBOTICS AND DATA SCIENCE Topic Coordinators Sara Degli Esposti ( IPP-CCHS, CSIC ) and Carles Sierra ( IIIA, CSIC ) 18 CHALLENGE 1 INTEGRATING KNOWLEDGE, REASONING AND LEARNING Challenge Coordinators Felip ManyĂ ( IIIA, CSIC ) and AdriĂ ColomĂ© ( IRI, CSIC – UPC ) 38 CHALLENGE 2 MULTIAGENT SYSTEMS Challenge Coordinators N. Osman ( IIIA, CSIC ) and D. LĂłpez ( IFS, CSIC ) 54 CHALLENGE 3 MACHINE LEARNING AND DATA SCIENCE Challenge Coordinators J. J. Ramasco Sukia ( IFISC ) and L. Lloret Iglesias ( IFCA, CSIC ) 80 CHALLENGE 4 INTELLIGENT ROBOTICS Topic Coordinators G. AlenyĂ ( IRI, CSIC – UPC ) and J. Villagra ( CAR, CSIC ) 100 CHALLENGE 5 COMPUTATIONAL COGNITIVE MODELS Challenge Coordinators M. D. del Castillo ( CAR, CSIC) and M. Schorlemmer ( IIIA, CSIC ) 120 CHALLENGE 6 ETHICAL, LEGAL, ECONOMIC, AND SOCIAL IMPLICATIONS Challenge Coordinators P. Noriega ( IIIA, CSIC ) and T. AusĂn ( IFS, CSIC ) 142 CHALLENGE 7 LOW-POWER SUSTAINABLE HARDWARE FOR AI Challenge Coordinators T. Serrano ( IMSE-CNM, CSIC – US ) and A. Oyanguren ( IFIC, CSIC - UV ) 160 CHALLENGE 8 SMART CYBERSECURITY Challenge Coordinators D. Arroyo Guardeño ( ITEFI, CSIC ) and P. Brox JimĂ©nez ( IMSE-CNM, CSIC – US )Peer reviewe