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Intrinsic motivations: announcement of several works
by Gianluca Baldassarre <gianluca.baldassarre＠istc.cnr.it> Feb. 16, 2015

Feb. 16, 2015

I announce the publication of various collections of papers and activities on intrinsic motivations (IMs). Please find below a list of brief explanations and links to them. Further below I also briefly introduce intrinsic motivations for those who are not familiar with them. *** Collections of papers and activities on IMs *** Lately I co-edited a special issue (`Topic') of Frontiers. The articles of the Topic were published in part with `Frontiers in Psychology - Cognitive Science' (19 articles): http://journal.frontiersin.org/ResearchTopic/1326 and in part with `Frontiers in Neurorobotics' (6 articles): http://journal.frontiersin.org/ResearchTopic/1797 All articles of the Topic, including an editorial that briefly introduces IMs and summarises the contributions, can be downloaded with one click from this web page as a `Frontiers eBook' (1 pdf file of 45 MB): http://www.frontiersin.org/books/Intrinsic_motivations_and_open-ended_devel… Before the Topic, we edited a Springer book collecting other 17 papers on IMs: `Baldassarre G., Mirolli M. (eds) (2013). Intrinsically motivated learning in natural and artificial systems. Berlin: Springer.' You can see the titles, abstracts, authors of the book chapters, and other information on the book, here: http://link.springer.com/book/10.1007%2F978-3-642-32375-1 We also edited a second Springer book collecting further 14 papers: `Baldassarre G., Mirolli M. (eds) (2013). Computational and Robotic Models of the Hierarchical Organisation of Behaviour. Berlin: Springer-Verlag.' Hierarchical architectures represent a key problem for IMs as the knowledge and skills accumulated under the drive of IMs has to be stored in suitable hierarchical systems. You can see the titles, abstracts and authors of the book chapters, and other information on the book, here: http://link.springer.com/book/10.1007/978-3-642-39875-9 The three collections above were prompted and partially funded by a 4-year EU-funded project, now terminated, called `IM-CLeVeR -- Intrinsically Motivated Cumulative Learning Robots'. The project was funded by the European Commission under the 7th Framework Programme (FP7/2007-2013), ICT Challenge 2 `Cognitive Systems and Robotics' (grant agreement no. ICT-IP-231722). The web-site of the project is here: http://www.im-clever.eu/ In the project web-site you can find information on the project activities and other material on IMs, for example a summary of main results and publications of the project: http://www.im-clever.eu/project/final-results a final digest of the project insights: http://www.im-clever.eu/project/final-digest/final-digest and a `tool-box' of information for those who are interested in IMs: http://www.im-clever.eu/project/final-toolbox/final-toolbox I hope these works contribute to attract an increasing attention of... clever and strongly intrinsically-motivated researchers from different disciplines on intrinsic motivations, a great topic of investigation so important for humans and for technology. *** Brief introduction to intrinsic motivations (IMs) *** Intrinsic motivations are related to things such as curiosity, the interest for novel stimuli and surprising events, and the motivation to learn new behaviours (think about children at play). It has been proposed that the adaptive value of IMs is to motivate and guide the cumulative acquisition of knowledge and skills that can be later used (e.g., in adulthood) to accomplish goals that enhance biological fitness. IMs continue to operate also during adulthood and indeed in humans they underlie life-long learning and typically human activities such as art and scientiﬁc discovery. IMs are also at the core of processes that strongly aﬀect human well-being, such as the sense of competence, self-determination, and self-esteem. Recent neuroscientiﬁc research is starting to uncover the basic brain mechanisms underlying IMs, although under research agendas not directly addressing IMs. For example, IM mechanisms have been related to learning signals based on dopamine, novelty detection in hippocampus, and prediction errors in various parts of brain. In the last decade, IMs have also been introduced in machine learning and autonomous robotics as a means for developing artiﬁcial systems that can autonomously learn several diﬀerent skills in an open-ended, cumulative fashion. The idea is that intelligent machines and robots could autonomously acquire skills and knowledge under the guidance of IMs, and later exploit such knowledge and skills to accomplish the tasks that are useful for the user in more eﬃcient and faster ways than if they had to acquire them from scratch. This possibility would especially enhance the utility of intelligent artiﬁcial systems when operating in real-life environments posing challenges that cannot be foreseen at design time. Although the possible functions and mechanisms of IMs are still debated and seen differently by the different research communities involved, and although the recognition of IMs as a research field per se is only partially accomplished, their link with some of the most sophisticated aspects of human cognition (curiosity, art, science, well-being), and their potential for applications make them an interesting and important research field that deserves additional research efforts. Kind Regards, Gianluca Baldassarre -- .|.CS...|.......|...............|..|......US.|||.|||||.||.||||..|...|....... Gianluca Baldassarre, Ph.D., Laboratory of Computational Embodied Neuroscience, Istituto di Scienze e Tecnologie della Cognizione, Consiglio Nazionale delle Ricerche (LOCEN-ISTC-CNR), Via San Martino della Battaglia 44, I-00185 Roma, Italy E-mail: gianluca.baldassarre(a)istc.cnr.it Web: http://www.istc.cnr.it/people/gianluca-baldassarre Tel: +39 06 44 595 231 Fax: +39 06 44 595 243 Learn from the past, live in(tensely) the present, dream for the future ...CS.|||.||.|||.||..|.......|........|...US.|.|....||..|..|......|.........

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Subject: ECMLPKDD 2015 : Call for Papers, Tutorials and Workshops
by ECMLPKDD 2015 Feb. 16, 2015

Feb. 16, 2015

The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD) will take place in Porto, Portugal, from September 7th to 11th, 2015 (http://www.ecmlpkdd2015.org) This event is the leading European scientific event on machine learning and data mining and builds upon a very successful series of 25 ECML and 18 PKDD conferences, which have been jointly organized for the past 14 years. ECMLPKDD 2015 will host three tracks, tutorials and a set of workshops. Therefore, we invite all researchers and practitioners from different communities to submit papers and/or present tutorial and workshop proposals. ************************* CALL FOR PAPERS ************************* JOURNAL TRACK ********************* Articles for this track are submitted all year long directly to either Machine Learning or Data Mining and Knowledge Discovery, and are reviewed like regular journal articles. Accepted articles appear in full in the journal and the authors are given a presentation slot at the conference. Articles deemed insufficiently mature for journal publication may be accepted for inclusion in the proceedings. Submissions to the journal track will be managed by the Guest Editorial Board. Paper Submission: Cut-off dates for the bi-weekly batches are 18 Jan, 1 Feb, 15 Fev, 1 Mar, 15 Mar, 29 Mar, 12 Apr, 26 Apr of 2015 Web Page: http://www.ecmlpkdd2015.org/submission/journal-track RESEARCH PROCEEDINGS TRACK ******************************************* The research proceedings track, which is organized in the traditional way. Accepted papers will be published in the Lecture Notes in Artificial Intelligence (LNCS/LNAI) of Springer, after reviewing by the programme committee. Abstract Submission Deadline: March 26, 2015 Paper Submission Deadline: April 2, 2015 Paper Acceptance Notification: June 1, 2015 Paper Camera Ready Submission: June 15, 2015 Web Page: http://www.ecmlpkdd2015.org/submission/research-proceedings-track INDUSTRIAL, GOVERNMENTAL & NON-GOVERNMENTAL PROCEEDINGS TRACK **************************************************************************** ************************** The NEW industrial, governmental & non-governmental (NGO) proceedings track is independent and distinct from the Research Track. Submissions to this track should solve real-world problems and focus on engineering systems, applications, and challenges. Accepted papers will be published in the Lecture Notes in Artificial Intelligence (LNCS/LNAI) of Springer, after reviewing by the programme committee. Abstract Submission Deadline: March 26, 2015 Paper Submission Deadline: April 2, 2015 Paper Acceptance Notification: June 1, 2015 Paper Camera Ready Submission: June 15, 2015 Web Page: http://www.ecmlpkdd2015.org/submission/industrial-proceedings-track ***************************************************************** CALL FOR TUTORIAL AND WORKSHOP PROPOSALS ***************************************************************** TUTORIALS ************** The tutorials are intended to provide a comprehensive introduction to established or emerging research topics of interest for the machine learning and the data mining community. These topics include related research fields or applications. The ideal tutorial should attract a wide audience. It should be broad enough to provide a basic introduction to the chosen research area, but it should also cover the most important topics in depth. We welcome half day workshop proposals. Proposal Deadline: March 2, 2015 Proposal Acceptance Notification: March 23, 2015 Web Page: http://www.ecmlpkdd2015.org/submission/call-for-tutorials WORKSHOPS **************** The workshops will be on relevant and current topics in Machine Learning and Data Mining. The scope of the proposal should be consistent with the conference themes as described in the ECMLPKDD 2015 Call for Papers (http://www.ecmlpkdd2015.org/submission) Interdisciplinary workshops that bring together researchers and practitioners from different communities are especially welcome. We encourage workshops that bridge the gap between theoretical advances and important and/or innovative applications of machine learning and data mining. We welcome both full and half day workshop proposals. Proposal Deadline: March 2, 2015 Proposal Acceptance Notification: March 23, 2015 Workshop Websites and Call for Papers Online: March 27, 2015 Workshop Proceedings (Camera-ready): August 3, 2015 Web Page: http://www.ecmlpkdd2015.org/submission/call-for-workshop-proposals Hope to see you all soon in Porto, Portugal!!! The publicity chairs of the ECMLPKDD 2015, Carlos Abreu Ferreira Ricardo Campos --- Este e-mail foi verificado em termos de vírus pelo software antivírus Avast. http://www.avast.com

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Subject:SAMSI CCNS Computational Neuroscience Summer School:July 27-31, 2015
by Zhu, Hongtu Feb. 14, 2015

Feb. 14, 2015

> > > >Dear colleagues, > >It is my pleasure to announce the 2015 CCNS Summer School on Computational >Neuroscience. This week-long program will be held on July 27-31,2015 as >part of the 2015-16 program on Challenges in Computational Neuroscience >(CCNS) at the Statistical and Applied Mathematical Sciences Institute >(SAMSI) in Research Triangle Park, North Carolina, USA. >( http://www.samsi.info/CCNS ) > > >The school will include courses on five major research topics in >computational neuroscience by the following instructors: > >* Neural Spike Train Analysis > Mark A. Kramer, Boston University > Uri Eden, Boston University >* Compressed Sensing for Signal Processing > Justin Romberg, Georgia Tech >* Functional Data Analysis for Medical Imaging Data > Hans-Georg Muller, University of California, Davis > Jane-Ling Wang, University of California, Davis >* Big-biomedical Data Integration and Analysis > Jeffrey S. Morris, MD Anderson Cancer Center, University of Texas > Hongtu Zhu, University of North Carolina-Chapel Hill > Yu-Ping Wang, Tulane University >* Shape Analysis and Diffeomorphisms for Medical Imaging Data > Laurent Younes, Johns Hopkins University > >The instructors will give an in-depth overview of each topic followed by >problem/discussion sessions. Software packages will be introduced to >students with datasets to carry out some simple data analysis. This summer >school is targeted for graduate students, postdocs, and junior faculty >from neuroscience, biomedical engineering, radiology, statistics, >and applied mathematics. We may consider a limited number of applications >from senior faculty. > >The application deadline is Monday, June 1, 2015 > >For further information and to apply, see: > http://www.samsi.info/ccns-summer > >or email questions to CCNS(a)samsi.info

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Postdoctoral Fellowships in in System and Computational Neuroscience
by Majid Mohajerani Feb. 14, 2015

Feb. 14, 2015

Postdoctoral Fellowships in System and Computational Neuroscience, University of Lethbridge A position as Postdoctoral Fellow is now open for an outstanding postdoctoral associate to conduct research in the field of neural network functions at the Canadian Centre for Behavioural Neuroscience at the University of Lethbridge, in Lethbridge, Canada. Our goal is to understand cellular and brain system mechanisms of memory and memory disorders associated with aging and brain damage. Brain regions to be investigated include frontal, parietal cortex and hippocampus, with a view to achieving a whole picture of how these brain structures work together dynamically to process, store, and transfer information to one another. The project is a collaborative effort between the research groups of Majid Mohajerani and Bruce McNaughton. Applicants are welcome to contact one of the investigators for more information. Successful candidates will join the highly collaborative and interdisciplinary Brain Dynamics group (http://lethbridgebraindynamics.com/) which has outstanding research strengths in the areas of learning and memory, decision making, information coding and related diseases such as Alzheimer's, schizophrenia, addiction and stroke. Salary scales will be competitive with NIH standards for postdoctoral researchers. Post-doctoral fellow with experience in in-vivo imaging techniques and two-photon imaging, in particular, will be an ideal candidate. Good communication skills are a must. Experience in MATLAB will be an asset. Candidates should be prepared to learn and use cutting-edge physiological, anatomical, and computational techniques, such as virtual reality-based rodent behavioral systems, optogenetic manipulations, and statistical methods for the analysis and modeling of data. This research will be supported by state-of-the-art facilities in the Canadian Centre for Behavioural Neuroscience, including advanced two-photon imaging, voltage sensitive dye imaging, and high density multi-unit electrophysiological recording and optogenetic techniques. Interested applicants must send an email to Dr. Mohajerani ( <mailto:mohajerani@uleth.ca> mohajerani(a)uleth.ca) and include a cover letter, curriculum vitae, a brief statement of research interests, and contact information of three references. Majid H. Mohajerani, PhD. Canadian Centre for Behavioural Neuroscience The University of Lethbridge 4401 University Dr W Lethbridge, AB T1K 3M4 Canada Office: +1(403)394-3950 Lab: +1(403)394-3951 Fax: +1(403)329-2775

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Job Announcement: Chief, Theoretical and Computational Neuroscience Research Program, NIH
by Dennis Glanzman Feb. 14, 2015

Feb. 14, 2015

Dear Colleagues, After 23 years running this program I retired from the NIH effective December 31, 2014. The position is expected to be filled soon, and the announcement should be posted on the NIH Jobs website next week. *"NIH anticipates a recruitment announcement for health science administrators (program officers) in the following areas of science: neurosciences, computational neuroscience, computational biology, neurocircuits, cognitive neuroscience. Please check http://www.jobs.nih.gov/globalrecruitment/ <http://www.jobs.nih.gov/globalrecruitment/> for the additional information and upcoming announcements."* It's been a great pleasure working with all of you in the Computational Neuroscience community! -- Dennis Glanzman

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New book "Understanding Vision: theory, models, and data"
by Zhaoping Li Feb. 13, 2015

Feb. 13, 2015

This book "Understanding Vision: theory, models, and data" is published by Oxford University Press in May 2014 and, by now, it is available from various online sites and shops worldwide. For more information, go to http://www0.cs.ucl.ac.uk/staff/zhaoping.li/VisionBook.html The book's Table of Contents can be viewed at http://www0.cs.ucl.ac.uk/staff/zhaoping.li/prints/TableOfContents.pdf Teaching and learning support for the book (e.g., ppt files for the figures in the book) is also available and will be updated at http://www0.cs.ucl.ac.uk/staff/zhaoping.li/VisionBook.html . Readership: Computational neuroscientists, visual psychologists/cognitive scientists, Visual neuroscientists/physiologists/anatomists, Researchers in machine vision or computer vision or robot vision The book is written in such a way that vision scientists, unfamiliar with mathematical details, should be able to conceptually follow the theoretical principles and their relationship with physiological, anatomical, and psychological observations, without going through the more mathematical pages. For those with a physical science background, especially those from machine vision, this book serves as an analytical introduction to biological vision. It can be used as a textbook or a reference book in a vision course, or a computational neuroscience course for graduate students or advanced undergraduate students. It is also suitable for self-learning by motivated readers. In addition, for those with a focused interest in just one of the topics in the book, it is feasible to read just the chapter on this topic without having read or fully comprehended the other chapters. In particular, Chapter 2 presents a brief overview of experimental observations on biological vision; Chapter 3 is on encoding of visual inputs, Chapter 5 is on visual attentional selection driven by sensory inputs, and Chapter 6 is on visual perception or decoding. Please let me know if you need more information. best wishes, Li Zhaoping

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NIH recruiting program officers in computational neuroscience
by Giancarlo La Camera Feb. 13, 2015

Feb. 13, 2015

(Posted on behalf of Janine Simmons @ NIMH, details below) NIH anticipates recruitment announcement for health science administrator (program officers) in the following areas of science: neurosciences, computational neuroscience, computational biology, neurocircuits, cognitive neuroscience. Please check http://www.jobs.nih.gov/globalrecruitment/ for additional information and upcoming announcements. Please note that the potential position will be included in an HHS-wide announcement to be open *Feb 17-26, 2015* (note the brief time window). Please share this information widely with any PhD-level scientists with appropriate expertise who may be interested in joining an extramural funding team. I am also happy to provide additional information to interested potential applicants. Thanks, Janine -- Janine M. Simmons, M.D., Ph.D. Affect, Social Behavior & Social Cognition Program National Institute of Mental Health (301) 443-1576

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Postdoctoral position in computational/theoretical neuroscience
by Odelia Schwartz Feb. 13, 2015

Feb. 13, 2015

Applications are invited for a postdoctoral position in computational/theoretical neuroscience, in the lab of Odelia Schwartz at the University of Miami. Our lab employs tools of computational and theoretical neuroscience, to study systems from the neural level through to perception and behavior. For example, we develop models of sensory processing based on the hypothesis that images, movies, and sounds have predictable and quantifiable statistical regularities to which the brain is sensitive. The models are constructed through interplay with physiological and psychophysical data. Example projects include but are not limited to: (1) Modeling of how neurons and percepts are affected by contextual information in time dynamically; (2) Modeling of hierarchical cortical processing. For more information about the lab and recent publications, see: http://www.cs.miami.edu/~odelia/ The candidate should have a Ph.D. in a relevant discipline, a strong quantitative background, and an interest in neuroscience. Prior experience would ideally include areas such as computational neuroscience, machine learning, statistics and/or signal processing. University of Miami offers a vibrant interdisciplinary environment, with a growing emphasis on a brain sciences initiative. The position will be in the Department of Computer Science, with opportunities to collaborate with Psychology, Biology and the School of Medicine. The university is located in beautiful Coral Gables, and surrounded by Miami. Initial appointment is for one year with possible yearly renewal for a total period of three years. Salary is competitive and will be commensurate with experience. Please apply online for position # 050932 : UM Careers website http://um.hodesiq.com/job_start.asp Send inquiries; or a CV, a short statement of research interests, and names and contact information of 3 references to: Odelia Schwartz odelia(a)cs.miami.edu The University of Miami offers competitive salaries and a comprehensive benefits package including medical and dental benefits, tuition remission, vacation, paid holidays and much more. The University of Miami is an Equal Opportunity/Affirmative Action Employer. The University of Miami is an Equal Opportunity Employer - Females/Minorities/Protected Veterans/Individuals with Disabilities are encouraged to apply. Applicants and employees are protected from discrimination based on certain categories protected by Federal law.

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Deadline for RLDM2015 *postponed* to 20th Feb, midnight EST
by Yael Niv Feb. 13, 2015

Feb. 13, 2015

In response to a number of requests, we have, exceptionally, postponed the deadline for submission of abstracts to RLDM2025 by one week, to midnight EST on the 20th Feb 2015. We apologise for the short notice. Do please submit - and we hope to see you in Edmonton in June! -------------------------------- The 2nd Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM2015) www.rldm.org<http://www.rldm.org/> June 7-10, The University of Alberta, Edmonton, Alberta, Canada ====================================================== Submissions to RLDM2015 are now being accepted at https://cmt.research.microsoft.com/RLDM2015 Deadline: 20th February 2015, midnight EST We invite extended abstracts for contributed poster presentations and oral presentations. We welcome submissions of original research related to “learning and decision making over time to achieve a goal”, coming from any discipline or disciplines, describing empirical results from human, animal or animat experiments, and/or theoretical work, simulations and modeling. Contributions should be aimed at an interdisciplinary audience, but not at the expense of technical excellence. This is an abstract-based meeting, with no published conference proceedings. As such, work that is intended for, or has been submitted to, other conferences or journals is also welcome, provided that the intent of communication to other disciplines is clear. Submissions should consist of a summary (max 2000 characters; text only), and an extended abstract of between one and four pages (including figures and references). LaTeX and RTF templates, and sample submissions, are available from http://rldm.org/rldm2015/submission-procedure/ Note: Only the summary will be made available in the (electronic) abstract booklets. The extended abstract will be used for reviewing, and will be available online only pending on authors’ separate explicit permission. Online availability will have no bearing on the review process and authors are encouraged to include new, unpublished, findings which they do not want to make publicly available. To submit your abstract please go to https://cmt.research.microsoft.com/RLDM2015 Submissions will be reviewed for relevance to the topic and for quality. Exceptional abstracts will be selected for oral presentations and for poster spotlight presentations. IMPORTANT DATES: Submissions close: 20 Feb 2015, 11:59pm EST Notification of acceptance: by March 28, 2015 (expedited reviewing for those needing an international visa can be requested) Early registration: 28 April 2015 (see http://rldm.org/rldm2015/registration/) Meeting: 7-10 June 2015, Edmonton, Alberta (*NEW* this year: Tutorials on the 7th) RLDM2015 Invited speakers: http://rldm.org/rldm2015/invited-speakers2015/ RLDM2015 Tutorials: http://rldm.org/rldm2015/tutorials/ RLDM2015 Programme Committee: http://rldm.org/rldm2015/committees/rldm2015-program-committee/

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[CfP SASO'2015] 21-25 September 2015 - Boston Massachusetts
by Frédéric Armetta Feb. 13, 2015

Feb. 13, 2015

****************************************************************************************** CALL FOR PAPERS The Ninth IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2015) Boston Massachusetts; 21-25 September 2015 https://saso2015.mit.edu/ ****************************************************************************************** Part of FAS* - Foundation and Applications of Self* Computing Conferences Collocated with: The International Conference on Cloud and Autonomic Computing (CAC 2015) The 15th IEEE Peer-to-Peer Computing Conference (P2P 2015) ------------------- Aims and Scope ------------------- The aim of the Self-Adaptive and Self-Organizing systems conference series (SASO) is to provide a forum for the foundations of a principled approach to engineering systems, networks and services based on self-adaptation and self-organization. The complexity of current and emerging networks, software and services, especially in dealing with dynamics in the environment and problem domain, has led the software engineering, distributed systems and management communities to look for inspiration in diverse fields (e.g., complex systems, control theory, artificial intelligence, sociology, and biology) to find new ways of designing and managing such computing systems. In this endeavor, self-organization and self-adaptation have emerged as two promising interrelated approaches. They form the basis for many other self-* properties, such as self-configuration, self-healing, or self-optimization. Systems exhibiting such properties are often referred to as self-* systems. The ninth edition of the SASO conference embraces the inter-disciplinarity and the scientific, empirical, and application dimensions of self-* systems and welcomes novel results on both self-adaptive and self-organizing systems research. The topics of interest include, but are not limited to: - Self-* systems theory: theoretical frameworks and models; biologically- and socially-inspired paradigms; inter-operation of self-* mechanisms; - Self-* systems engineering: reusable mechanisms, design patterns, architectures, methodologies; software and middleware development frameworks and methods, platforms and toolkits; hardware; self-* materials; - Self-* system properties: robustness, resilience and stability; emergence; computational awareness and self-awareness; reflection; - Self-* cyber-physical and socio-technical systems: human factors and visualization; self-* social computers; crowdsourcing and collective awareness; human-in-the-loop; - Applications and experiences of self-* systems: cyber security, transportation, computational sustainability, big data and creative commons, power systems; swarm systems and robotics. - Self-* in education: experience reports; curricula; innovative course concepts; methodological aspects of self-* systems education Contributions must present novel theoretical or experimental results; novel design patterns, mechanisms, system architectures, frameworks or tools; or practical approaches and experiences in building or deploying real-world systems and applications. Contributions contrasting different approaches for engineering a given family of systems, or demonstrating the applicability of a certain approach for different systems, are equally encouraged. Likewise, papers describing substantial innovation or insights in the use and communication of self-* systems in the classroom are welcome. Where relevant and appropriate, accepted papers will also be encouraged to participate in the Demo or Poster Sessions. -------------------- Important Dates -------------------- Abstract submission: May 8, 2015 Paper submission: May 22, 2015 (There will be no extensions of this deadline!) Notification: June 30, 2015 Camera ready copy due: July 17, 2015 Conference: September 21-25, 2015 ---------------------------- Submission Instructions ---------------------------- All submissions should be 10 pages and formatted according to the IEEE Computer Society Press proceedings style guide and submitted electronically in PDF format. Please register as authors and submit your papers using the SASO 2015 conference management system that will be announced on the website. The proceedings will be published by IEEE Computer Society Press, and made available as a part of the IEEE Digital Library. Note that a separate Call for Poster Submissions will also be issued. --------------------- Review Criteria --------------------- Papers should present novel ideas in the cross-disciplinary research context described in this call, clearly motivated by problems from current practice or applied research. We expect both theoretical and empirical contributions to be clearly stated, substantiated by formal analysis, simulation, experimental evaluations, comparative studies, and so on. Appropriate reference must be made to related work. Because SASO is a cross-disciplinary conference, papers must be intelligible and relevant to researchers who are not members of the same specialized sub-field. Authors are also encouraged to submit papers describing applications. Application papers are expected to provide an indication of the real world relevance of the problem that is solved, including a description of the deployment domain, and some form of evaluation of performance, usability, or comparison to alternative approaches. Experience papers are also welcome but they must clearly state the insight into any aspect of design, implementation or management of self-* systems which is of benefit to practitioners and the SASO community. ------------------------------- Conference General Chairs ------------------------------- Howard E Shrobe MIT CSAIL, Cambridge, MA, USA Julie A McCann Imperial College London, UK -------------------- Program Chairs -------------------- Emma Hart Edinburgh Napier University Gregory Sullivan BAE Systems AIT Jan-Philipp Steghöfer University of Gothenburg, Sweden

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