DOCSLIB.ORG

AAAI 2016 Executive Council Candidates PRESIDENT-‐ELECT

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
AAAI 2016 Executive Council Candidates PRESIDENT-‐ELECT AAAI 2016 Executive Council Candidates PRESIDENT-ELECT (2) Rina Dechter Rina Dechter is a professor of Computer Science at the University of California, Irvine. She received her PhD in Computer Science at UCLA in 1985, an MS degree in Applied Mathematics from the Weizmann Institute and a B.S in Mathematics and Statistics from the Hebrew University, Jerusalem. Her research centers on computational aspects of automated reasoning and knowledge representation including search, constraint processing and probabilistic reasoning. Professor Dechter is an author of ‘Constraint Processing’ published by Morgan Kaufmann, 2003, and ‘Reasoning with Probabilistic and Deterministic Graphical Models: Exact Algorithms’ by Morgan and Claypool publishers, 2013, has co-authored over 150 research papers, and has served on the editorial boards of: Artificial Intelligence, the Constraint Journal, Journal of Artificial Intelligence Research, Logical Methods in Computer Science (LMCS) and journal of Machine Learning (JLMR). She is a fellow of AAAI, a Radcliffe Fellow 2005-2006, received the 2007 Association of Constraint Programming (ACP) research excellence award and is a 2013 Fellow of the ACM. She served as the Program co-chair of AAAI 2002 and as a AAAI councilor, as Program Chair of CP-2000 and Program co-chair of UAI-2006. She has been Co-Editor-in-Chief of Artificial Intelligence, since 2011. Statement AAAI is the leading organization promoting scientific research and education in artificial intelligence. It has been my professional home for more than 30 years, and I am honored to be considered for this leadership position. If elected, I will dedicate myself to giving back and advancing the mission of an organization that has enabled me—and countless others—to collaborate with colleagues in world-class conferences, workshops, and symposia. My primary goal as president will be to encourage and facilitate greater interaction among AI’s subfields. While progress made in some of these subfields is remarkable, our ultimate goal is to assemble all the pieces in a universal intelligent agent, incorporating vision, speech, natural language processing, machine learning, planning, knowledge representation and reasoning. This goal requires extensive cooperation and collaboration and can only be facilitated by having all AI’s parts interact through a unified language and under a single supportive umbrella. AAAI is the organization best positioned to facilitate that ongoing integration project, but it must be a constant priority. AAAI must also remain agile in order to handle emerging issues in a timely manner. I would strive to ensure that AAAI is the key global platform for an ongoing discussion on AI’s future, facilitated through workshops, panels, and articles in the AI magazine and elsewhere. We have a pivotal role in helping shape future research directions and in providing public education. Moreover, AAAI can and should encourage inclusion in the field, and continue to offer leadership in promoting diversity through training and education. Finally, AAAI should continue to broaden its outreach to the international community, especially in order to bring the potentially beneficial impact of AI to the emerging world. To make progress on this agenda, AAAI must be sustained and strengthened by a growing membership. I recognize and embrace the fact that an essential focus of AAAI leadership must be to increase membership by encouraging young researchers to join, in the legacy communities of North America and Europe—and even more so in Asia and the Middle East. Thank you for your consideration. Yolanda Gil Yolanda Gil is Director of Knowledge Technologies at the Information Sciences Institute of the University of Southern California, and Research Professor in Computer Science. She received her M.S. and Ph. D. degrees in Computer Science from Carnegie Mellon University. Her research is in intelligent user interfaces, knowledge-rich collaborative problem solving, and the semantic web. A recent focus is scientific data analysis through semantic workflows. She initiated and chaired the W3C Provenance Group that led to a community standard in this area. She served in the Advisory Committee of the Computer Science and Engineering Directorate of the NSF. She is Chair of ACM SIGAI, the Association for Computing Machinery's Special Interest Group on Artificial Intelligence, and is on the Editorial Board of the Artificial Intelligence journal. She was elected Fellow of AAAI in 2012. Statement AAAI is a fantastic organization that greatly benefits our field. I understand how it serves our community from many perspectives, having started as a student volunteer and then author, workshop and symposium organizer, AAAI program co-chair, and finally councilor and AAAI conference committee chair. I have always been impressed by the enthusiasm and creativity of my colleagues in making AAAI a vibrant community. Looking forward, I believe AAAI needs to have a greater presence in the broader science ecosystem and propose here some possibilities. First, I believe AAAI needs to join science initiatives in reproducibility and digital scholarship. From ACM to AAAS, many scientific organizations and conferences are improving the accessibility and persistence of digital research products beyond published articles. Science communities are recommending repositories and best practices for sharing data, software, workflows, and other resources in ways that promote reusability and author credit. AAAI must create best practices for our field, and in doing so it will make our research more visible in other communities. Second, AAAI could do more to promote younger AI researchers. We need to instate a Dissertation Award, if possible in cooperation with ACM SIGAI to raise its visibility in the broader CS community. We should include an Early Career Researcher Keynote at AAAI, and profile young researchers in AI Magazine. We should have a registry of AI thesis abstracts to promote the important ideas that PhD students contribute to our field. I have been a judge for AAAI at the ISEF high school science competition, and have seen that two thirds of their CS projects are actually in AI. One student reported that his hobby is reading AI papers from the 60s. There is tremendous interest that we need to capitalize on to attract the best talent to our field. Finally, I think that we can do more to give AI higher visibility and stronger ties with the CS and science community. AAAI could work with ACM, AAAS, and other organizations to promote AI and involve AI researchers in the broader discussions that are taking place about the future of intelligent systems, autonomy, computer-mediated interactions, and big data in the broader science, government, and social context. EXECUTIVE COUNCILOR (8) Blai Bonet Blai Bonet is a professor in the computer science department at Universidad Simon Bolivar, Venezuela. He received his Ph.D. in computer science from the University of California, Los Angeles. His research are in the areas of automated planning, heuristic search and knowledge representation. He has received six best paper awards or honorable mentions, including the 2009 and 2014 ICAPS Influential Paper Awards. Blai Bonet is a co-author (with Hector Geffner) of the book titled "A Concise Introduction to Models and Methods for Automated Planning." Blai Bonet is an associate editor of Artificial Intelligence and the Journal of Artificial Intelligence Research, and served as conference co-chair of ICAPS-12 and program co-chair of AAAI-15. Statement Fragmentation and internationalization are the biggest challenges for AAAI over the next few years. The high success of fragmented areas such a ML, NLP, Vision and robotics is affecting traditional AI core areas in many respects, from insufficiency of funds and difficulty to attract the best students to lack of incentives and loss of researchers. On the other hand, the sudden growth of conferences like NIPS and AAMAS, and IJCAI's change of schedule put more pressure on AAAI on how to sustain and even increase its status as the main conference in AI, worldwide. Fortunately, we have seen in the two last AAAI conferences very good signs and opportunities that need to be leveraged for handling these challenges. We saw an incredible increase on the number of submissions and international participants, and on the number of submissions in the fragmented areas. So, AAAI is healthy and strong as an organization but it needs to prepare itself for the times ahead. Discussions on issues such as international representation inside the different committees, internationalization of conferences, and joint ventures with fragmented areas may prove instrumental for making the right decisions. J. Christopher Beck Chris Beck (PhD University of Toronto, 1999) is a Professor in the Department of Mechanical & Industrial Engineering at the University of Toronto. Prior to (re)joining UofT, he was a Staff Scientist at the Cork Constraint Computation Centre, Ireland and a Senior Scientist at ILOG, France. He has been conducting research since 1992 in both AI and Operations Research, focusing on planning and scheduling, constraint programming, and optimization. He has over 100 peer-reviewed publications and has given over 100 scholarly presentations in 17 countries. Chris is the President of the Executive Council for the International Conference on Automated Planning and Scheduling and Associate Editor or member of the Editorial Board for the Journal of Artificial Intelligence Research (since 2010), Constraints (2008-2013), Journal of Scheduling (2005-2012), and The Knowledge Engineering Review (2005-2015). He has served as the Program/Conference Chair/Co-chair of CPAIOR (2006, 2011), ICAPS (2008), and SARA (2009) and will be the Program Chair for CP2017. Statement While AI becomes increasingly a part of our lives and as society raises important concerns about its implications, AI researchers are fragmented by geography and sub-discipline and lack a unified voice in the media, on funding bodies, and in larger societal discussions. If AAAI wants to be (or be part of) a larger, international collective, I believe that it needs to re-examine its goals and develop paths toward them.
Load more

Recommended publications
  • Algorithms for Reasoning with Probabilistic Graphical Models INTRODUCTORY
    Rina Dechter & Alexander Ihler University of California, Irvine Algorithms for Reasoning with Probabilistic Graphical Models INTRODUCTORY Summary The course will cover the primary exact and approximate algorithms for reasoning with probabilistic graphical models (e.g., Bayesian and Markov networks, influence diagrams, and Markov decision processes). We will present inference-based, message passing schemes (e.g., variable elimination) and search-based, conditioning schemes (e.g., cycle-cutset conditioning and AND/OR search). Each algorithm class possesses distinct characteristics and in particular has different time vs. space behavior. We will emphasize the dependence of the methods on graph parameters such as the treewidth, cycle- cutset, and (pseudo-tree) height. We will start from exact algorithms and move to approximate schemes that are anytime, including weighted mini-bucket schemes with cost-shifting and MCMC sampling. Syllabus Class 1: Introduction and Inference schemes • Basic Graphical models – Queries – Examples/applications/tasks – Algorithms overview • Inference algorithms, exact – Bucket elimination – Jointree clustering – Elimination orders • Decomposition Bounds – Dual Decomposition, GDD – MBE/WMBE – Belief Propagation Class 2: Search Schemes • AND/OR search spaces, pseudo-trees – AND/OR search trees – AND/OR search graphs – Generating good pseudo-trees • Heuristic search for AND/OR spaces – Brute-force traversal – Depth-first AND/OR branch and bound – Best-first AND/OR search – The Guiding MBE heuristic – Marginal Map (max-sum-product) • Hybrids of search and Inference Class 3: • Variational methods – Convexity & decomposition bounds – Variational forms & the marginal polytope – Message passing algorithms – Convex duality relationships • Monte Carlo sampling – Basics – Importance sampling – Markov chain Monte Carlo – Integrating inference and sampling References Rina Dechter: Reasoning with Probabilistic and Deterministic Graphical Models: Exact Algorithms.
    [Show full text]
  • Felix Elwert
    July 2021 FELIX ELWERT University of Wisconsin–Madison Department of Sociology and Center for Demography and Ecology 4426 Sewell Social Sciences Building 1180 Observatory Drive Madison, WI 53706 [email protected] ACADEMIC POSITIONS University of Wisconsin–Madison 2017- Professor, Department of Sociology Department of Biostatistics and Medical Informatics (affiliated) Department of Population Health Sciences (affiliated) 2013–2017 Associate Professor (Affiliated), Department of Population Health Sciences 2012–2017 Associate Professor, Department of Sociology 2007–2012 Assistant Professor, Department of Sociology WZB Berlin Social Science Center, Germany 2015–2016 Acting Director, Research Unit Social Inequality and Social Policy 2014–2015 Karl W. Deutsch Visiting Professor Harvard Medical School 2006–2007 Postdoctoral Fellow, Department of Health Care Policy EDUCATION 2007 Ph.D., Sociology, Harvard University 2006 A.M., Statistics, Harvard University 1999 M.A., Sociology, New School for Social Research 1997 Vordiplom, Sociology, Free University of Berlin Felix Elwert / May 2020 AWARDS AND FELLOWSHIPS 2018 Leo Goodman Award, Methodology Section, American Sociological Association 2018 Elected member, Sociological Research Association 2018 Vilas Midcareer Faculty Award, University of Wisconsin-Madison 2017- H. I. Romnes Faculty Fellowship, University of Wisconsin-Madison 2016-2018 Fellow, WZB Berlin Social Science Center, Berlin, Germany 2013 Causality in Statistics Education Award, American Statistical Association 2013 Vilas Associate Award, University of Wisconsin–Madison 2012 Jane Addams Award (Best Paper), Community and Urban Sociology Section, American Sociological Association 2010 Gunther Beyer Award (Best Paper by a Young Scholar), European Association for Population Studies 2009, 2010, 2017 University Housing Honored Instructor Award, University of Wisconsin- Madison 2009 & 2010 Best Poster Awards, Annual Meeting of the Population Association of America 2005–2006 Eliot Fellowship, Harvard University 2004 Aage B.
    [Show full text]
  • Ucla Computer Science Depart "Tment
    THE UCLA COMPUTER SCIENCE DEPART"TMENT QUARTERLY THE DEPARTMENT AND ITS PEOPLE FALL 1987/WINTER 1988 VOL. 16 NO. 1 SCHOOL OF ENGINEERING AND APPLIED SCIENCE COMPUTER SCIENCE DEPARTMENT OFFICERS Dr. Gerald Estrin, Chair Dr. Jack W. Carlyle, Vice Chair, Planning & Resources Dr. Sheila Greibach, Vice Chair, Graduate Affairs Dr. Lawrence McNamee, Vice Chair, Undergraduate Affairs Mrs. Arlene C. Weber, Management Services Officer Room 3713 Boelter Hall QUARTERLY STAFF Dr. Sheila Greibach, Editor Ms. Marta Cervantes, Coordinator Material in this publication may not be reproduced without written permission of the Computer Science Department. Subscriptions to this publication are available at $20.00/year (three issues) by contacting Ms. Brenda Ramsey, UCLA Computer Science Department, 3713 Boelter Hall, Los Angeles, CA 90024-1596. THE UCLA COMPUTER SCIENCE DEPARTMENT QUARTERLY The Computer Science Department And Its People Fall Quarter 1987/Winter Quarter 1988 Vol. 16, No. 1 SCHOOL OF ENGINEERING AND APPLIED SCIENCE UNIVERSITY OF CALIFORNIA, LOS ANGELES Fall-Winfer CSD Quarterly CONTENTS COMPUTER SCIENCE AT UCLA AND COMPUTER SCIENCE IN THE UNITED STATES GeraldEstrin, Chair...................................................................................................... I THE UNIVERSITY CONTEXT .............................................................................................. 13 THE UCLA COMPUTER SCIENCE DEPARTMENT The Faculty A rane nf;ntraract Biographies .............................................................................................................................
    [Show full text]
  • Rina Dechter
    Rina Dechter Information and Computer Science Irvine, CA 92717 email: [email protected] www.ics.uci.edu/~ dechter 949-824-6556 Education • University of California, Los Angeles Computer Science, Major Field: Artificial Intelligence Ph.D. 1985 • Weizman Institute of Science, Rehovot, Israel Applied Mathematics M.S. 1976 • The Hebrew University of Jerusalem, Israel Mathematics and Statistics B.S. 1973 Work Experience • University of California, Irvine Information and Computer Science July 1996{present: Full Professor July 1992{1996: Associate Professor Oct 1990{1992: Assistant Professor • Technion, Israel Computer Science Department Oct 1988 - Sept 1990: Senior Lecturer, (equivalent to Assistant Profes- sor) 1 • Hughes Aircraft, Calabasas July 85 - Mar 88: Staff member, AI Center • University of California, Los Angeles Computer Science Department Oct 87 - Sept 88: Research Associate • University of California, Los Angeles Computer Science Department July 85 - Sept 87: Presidential Postdoctoral Scholar • IBM Scientific Center, Los Angeles, CA Sept 82 - Dec 84: Student member of Technical Staff, Robotic Project • University of California, Los Angeles Computer Science Department July 81 - Sept 85: Research Assistant Research in the areas of Communication Networks (1981-1982), and Artificial Intelligence (1982-85) • Perceptronics Inc. Woodland Hills, California Oct 78 - Mar 80: Research Mathematician Responsible for modeling, experimental design and computer simula- tions for Human-Resource Test and Evaluation for advanced weapon systems • Everyman's University, Tel-Aviv, Israel Apr 76 - Aug 78: Staff member Developed self-study programs for teaching college mathematics. Awards and Honors • 1986-87: UC Presidential Postdoctoral Fellowship. • 1990: Best Paper, Canadian AI Conference (CSCSI-90) for [C15,J10] • 1991: NSF Presidential Young Investigator.
    [Show full text]
  • Department of Computer Science
    University of California, Irvine 2016-2017 1 Department of Computer Science Alexandru Nicolau, Department Chair Rina Dechter, Department Vice Chair 3019 Donald Bren Hall 949-824-1546 http://www.cs.uci.edu/ Overview With 40 full-time faculty members, 300+ graduate students, and more than 2,000 undergraduates, we provide a world-class research environment spanning not only the core areas of computer science — including computer architecture, system software, networking and distributed computing, data and information systems, the theory of computation, artificial intelligence, and computer graphics — but also highly interdisciplinary programs, such as biomedical informatics, data mining, security and privacy, and ubiquitous computing. The diverse research interests of our faculty are reflected directly in our educational programs. Computer Science faculty teach most of the undergraduate and graduate courses for the degree programs in both Computer Science and Information & Computer Science. We jointly offer with our colleagues in The Henry Samueli School of Engineering an undergraduate degree in Computer Science and Engineering, as well as the graduate program in Networked Systems. We also have a major in Computer Game Science, jointly offered with the Department of Informatics. Our department collaborates with many other institutions in the United States and abroad, and its doors are always open to a multitude of visitors and collaborators from all corners of the globe. Undergraduate Major in Computer Science The Computer Science major emphasizes the principles of computing that underlie our modern world, and provides a strong foundational education to prepare students for the broad spectrum of careers in computing. This major can serve as preparation for either graduate study or a career in industry.
    [Show full text]
  • Donald Bren School of Information and Computer Sciences Donald Bren Hall Dedication
    Annual Report 2006-07 Donald Bren School of Information and Computer Sciences Donald Bren Hall Dedication. June 20, 2007. (L to R) Vice Chancellor Tom Mitchell, Brenda Drake, Chancellor Michael V. Drake, Donald Bren, and Dean Debra J. Richardson Dear Bren School Community, 2006-07 was an exciting academic year at UC Irvine’s Donald Bren School of Information and Computer Sciences. We had many successes and firsts as we moved into the new Donald Bren Hall and welcomed many new graduate and undergraduate students. Today, we are an academic community of more than 1,500 students, over 100 full-time faculty and staff, and approximately 7,000 alumni worldwide. In teaching and scholarship, we continue to be among the top in information and computer sciences. To add to our list of accolades, our Networked Systems program was just rated number one by Academic Analytics, in additino to being ranked third in Information Systems. 04 Bren School Faculty At the Bren School, we have a unique perspective on computing and 08 Department of Computer Science information technology, stimulating society daily. Our vibrant community, 10 Department of Informatics comprised of researchers and educators as well as industry-leading scholars, 12 Department of Statistics explores innovative topics ranging from building complete computer systems on 14 Center of Excellence chips smaller than a finger nail to developing user interface systems that allow 18 Student Affairs engineers on opposite sides of the world to collaborate effectively. 20 Business Office I invite you stay in touch with us throughout the year by subscribing to our RSS 21 Communications feed or visiting our Web site regularly (www.ics.uci.edu).
    [Show full text]
  • CV-Prof.-Rachel-Ben-Eliyahu-Zohary
    CURRICULUM VITAE Name: Ben Eliyahu- Zohary Rachel 1. Academic Education B.Sc. 1983, Mathematics and Computer Science, Hebrew University of Jerusalem, Jerusalem, Israel. Ph.D. 1993, Computer Science University of California, Los-Angeles, UCLA. Topic of Dissertation: Computational aspects of nonmonotonic Reasoning. Advisors: Professor Judea Pearl (UCLA) and Professor Rina Dechter (UCI). 2. Academic Employment 2006-present Associate Professor, Jerusalem College of Engineering, Jerusalem, Israel. 2003-present Head, Department of Software Engineering, Jerusalem College of Engineering, Jerusalem, Israel. (on sabbatical 2004-2005, 2012-2013) 2004-2005 Research and Teaching, Harvard Division of Engineering and Applied Sciences, Visiting Scholar. 2003-2006 Senior Lecturer, Jerusalem College of Engineering, Jerusalem, Israel. 2000-2010 Senior Lecturer, Department of Communication Systems Engineering, Ben- Gurion University of the Negev, Beer-Sheva, Israel. (on maternity leave 2002, on leave 2003-2006) 2000-2003 Head of study Programs Committee, Ben-Gurion University of the Negev, Beer-Sheva, Israel. 1995-1998 Lecturer, Department of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva, Israel. 1995-1998 Head of study Programs Committee, Ben-Gurion University of the Negev, Beer-Sheva, Israel. 1993-1995 Post-doctoral researcher, Faculty of Computer Science, Technion - Israel Institute of Technology, Haifa, Israel. 1990-1993 Research Assitant, Department of Computer Science - Cognitive Systems Laboratory, UCLA. 1988-1990 Teaching Assistant
    [Show full text]
  • Practical Tractability of CSPS by Higher Level Consistency and Tree Decomposition
    University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Computer Science and Engineering: Theses, Computer Science and Engineering, Department Dissertations, and Student Research of Spring 5-3-2013 Practical Tractability of CSPS by Higher Level Consistency and Tree Decomposition Shant Karakashian University of Nebraska-Lincoln, [email protected] Follow this and additional works at: https://digitalcommons.unl.edu/computerscidiss Part of the Artificial Intelligence and Robotics Commons Karakashian, Shant, "Practical Tractability of CSPS by Higher Level Consistency and Tree Decomposition" (2013). Computer Science and Engineering: Theses, Dissertations, and Student Research. 58. https://digitalcommons.unl.edu/computerscidiss/58 This Article is brought to you for free and open access by the Computer Science and Engineering, Department of at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Computer Science and Engineering: Theses, Dissertations, and Student Research by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. PRACTICAL TRACTABILITY OF CSPS BY HIGHER LEVEL CONSISTENCY AND TREE DECOMPOSITION by Shant Karakashian A DISSERTATION Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfilment of Requirements For the Degree of Doctor of Philosophy Major: Computer Science Under the Supervision of Professor Berthe Y. Choueiry Lincoln, Nebraska May, 2013 PRACTICAL TRACTABILITY OF CSPS BY HIGHER LEVEL CONSISTENCY AND TREE DECOMPOSITION Shant Karakashian, Ph. D. University of Nebraska, 2013 Adviser: Berthe Y. Choueiry Constraint Satisfaction is a flexible paradigm for modeling many decision problems in Engineering, Computer Science, and Management. Constraint Satisfaction Problems (CSPs) are in general N P -complete and are usually solved with search.
    [Show full text]
  • UC Irvine ICS Technical Reports
    UC Irvine ICS Technical Reports Title Working notes of the 1991 spring symposium on constraint-based reasoning Permalink https://escholarship.org/uc/item/5311p0gf Author Dechter, Rina Publication Date 1991-09-16 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Z 63 HoI t, Working Notes of the 1991 Spring Symposium on Constraint-Based Reasoning^ Rina Dechter September 16, 1991 Technical Report 91-65 1991 Spring Symposium Series Constraint-Based Reasoning Working Notes (Distribution limited to symposium attendees) March 26 - 28, 1991 Stanford University Sponsored by the American Association for Artificial Intelligence I WORKING NOTES AAAI SPRING SYMPOSIUM SERIES Symposium; Constraint-Based Reasoning Program Committee: Rina Dechter, UC Irvine, Cochair Sanjay Mittal, Metaphor Computer Systems, Cochair Alan Borning, University of Washington Mark Fox, Carnegie Mellon University Eugene Freuder, University of New Hampshire Joxan Jaffar, IBM T.J. Watson Research Center Alan Mackworth, University of British Columbia Judea Pearl, UC Los Angeles MARCH 26, 27, 28, 1991 STANFORD UNIVERSITY Table of Contents FOREWORJD i Theoretical Issues in Constraint Satisfaction The Logic of Constraint Satisfaction 1 Alan Mackworthj Department of Computer Science, University of British Columbia Constraint-Based Knowledge Acquisition 30 Eugene C. Freuder, Computer Science Department, University of New Hampshire Default Logic, Propositional Logic and Constraints 33 Rachel Ben-Eliyahu, Computer Science Department, University of California, Los Angeles, and Rina Dechter, Department of Information and Computer Science, University of California, Irvine Satisfiability and Reasoning with Inconsistent Beliefs Using Energy Minimization 47 Gadi Pinkas, Computer Science Department, Washington University Reasoning About Disjunctive Constraints 57 Can A. Baykan and Mark S.
    [Show full text]
  • Program & Exhibit Guide
    Program & Exhibit Guide EIGHTEENTH NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE (AAAI-02) FOURTEENTH CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE (IAAI-02) July 28-August 1, 2002 Shaw Conference Centre and Westin Edmonton Hotel Edmonton, Alberta, Canada SPONSORED BY THE AMERICAN ASSOCIATION FOR ARTIFICIAL INTELLIGENCE Cosponsored by ACM/SIGART, Alberta Informatics Circle of Research Excellence (iCORE), Defense Advanced Research Projects Agency (DARPA), NASA Ames Research Center, NSF's Directorate for Computer and Information Science and Engineering (CISE), Naval Research Laboratory In cooperation with The University of Alberta Contents Robot Challenge Cochairs Ben Kuipers, University of Texas at Austin and Acknowledgments / 2 Ashley Stroupe, Carnegie Mellon University Awards / 3 Conference at a Glance / 5 Robot Rescue Competition Cochairs DC-02 / 4 Jenn Casper, Mark Micire, and Robin Murphy, Exhibition / 18 University of South Florida General Information / 33 IAAI-02 Program / 13–15 Robot Host Competition Cochairs Intelligent Systems Demonstrations / 21 David Gustafson, Kansas State University and Invited Talks / 10 Francois Michaud, Universite de Sherbrooke Maps / 37–39 Robot Exhibition Cochairs National Botball Exhibition / 31 Ian Horswill and Christopher Dac Le, Poster Sessions / 3 Northwestern University Registration / 32 Robot Building Laboratory / 7 Mobile Robot Workshop Chair Robot Competition and Exhibition / 24 Bill Smart, Washington University St. Louis Special Events and Programs / 3–4 Special Meetings
    [Show full text]
  • S. Sloman-VITA
    S. Sloman-VITA June, 2021 CURRICULUM VITAE 1. Steven Sloman, Professor, Department of Cognitive, Linguistic, & Psychological Sciences, Brown University. 2. Home address: Providence, Rhode Island 02906 3. Education: B.Sc., University of Toronto, 1986, Psychology Ph.D., Stanford University, 1990, Psychology Dissertation topic: Memory and judgment processes 4. Professional Appointments: 1990-1992 Post-doctoral fellow, University of Michigan 1992-1998 Assistant Professor, Brown University 1998-2005 Associate Professor, Brown University 2005- Professor, Brown University 5. Completed Research a. Books and Special Issues J. Park, M. Lee, H. Choi, Y. Kwon, S. Sloman, & E. Halperin (Eds.). 2019 Annual Reports of Attitude of Koreans toward Peace and Reconciliation. Seoul: Korea Institute for National Unification. Sloman, S. A. & Weber, E. (Eds.) (2019). The Cognitive Science of Political Thought. Cognition, 188, 1-140. Sloman, S. A. & Fernbach, P. (2017). The Knowledge Illusion: Why We Never Think Alone. NY: Riverhead Press. (see https://sites.google.com/site/slomanlab/the-knowledge-illusion-in-the- news) Sloman, S. A. (Ed.) (2015). The Changing Face of Cognition. Cognition, 135. Sloman, S. A. & Pearl, J. (Eds.) (2013). Special issue of Cognitive Science on Counterfactuals. Cognitive Science, 37 (6). Sloman, S. A. (2005). Causal models: How we think about the world and its alternatives. New York: Oxford University Press. Sloman, S. A. & Rips, L. J. (Eds.) (1998) Rules versus similarity in human thinking. Special issue of Cognition, 65, 87-302. Also appears as Similarity and symbols in human thinking, Cambridge: MIT Press book. c. Refereed Journal Articles Fullerton, M., Rabb, N., Mamidipaka, S., Ungar, Lyle, & Sloman, S. (in press). Evidence against risk as a motivating driver of COVID-19 preventive behaviors in the U.S.
    [Show full text]
  • Identifying Independencies in Causal Graphs with Feedback P Aj
    420 Pearl and Dechter Identifying Independencies In Causal Graphs with Feedback Judea Pearl Rina Dechter Cognitive Systems Laboratory Information & Computer Science Computer Science Department University of California, Irvine University of California, Los Angeles, CA 90024 Irvine, CA 92717 [email protected]. edu rdechter@ics. uci. edu Abstract then we contrast these notions with those associated with recursive and nonrecursive causal models. The We show that the d-separation criterion con­ reader is encouraged to consult the example in section stitutes a valid test for conditional indepen­ 3.1, where these notions are given graphical represen­ dence relationships that are induced by feed­ tations. back systems involving discrete variables. 2.1 BAYESIAN NETWORKS INTRODUCTION 1 Definition 1 Let V :::::: {X 1, . .., Xn} be an ordered set of variables, and let P( v) be the joint probability dis­ It is well known that the d-separation test is sound tribution on these variables. A set of variables P Aj is and complete relative to the independencies as­ said to be Markovian parents of Xj if PAj is a minimal sumed in the construction of Bayesian networks set of predecessors of Xi that renders Xi independent [Verma and Pearl, 1988, Geiger et al., 1990]. In other of all its other predecessors. In other words, PAj is words, any d-separation condition in the network cor­ any subset of {X,, ... , Xj -d satisfying responds to a genuine independence condition in the P(xJIPai):::::: P(xilx,, . ,X -t) (1) underlying probability distribution and, conversely, j such that no proper subset of PAj satisfies Eq. (1).
    [Show full text]