Roads Scholars CMU COMPUTER SCIENTISTS TACKLE TRANSPORTATION NEEDS for PENNSYLVANIA’S GOVERNMENTS
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Catur Komputer Dari Wikipedia Bahasa Indonesia, Ensiklopedia Bebas
Deep Blue Dari Wikipedia bahasa Indonesia, ensiklopedia bebas Belum Diperiksa Deep Blue Deep Blue adalah sebuah komputer catur buatan IBM. Deep Blue adalah komputer pertama yang memenangkan sebuah permainan catur melawan seorang juara dunia (Garry Kasparov) dalam waktu standar sebuah turnamen catur. Kemenangan pertamanya (dalam pertandingan atau babak pertama) terjadi pada 10 Februari 1996, dan merupakan permainan yang sangat terkenal. Namun Kasparov kemudian memenangkan 3 pertandingan lainnya dan memperoleh hasil remis pada 2 pertandingan selanjutnya, sehingga mengalahkan Deep Blue dengan hasil 4-2. Deep Blue lalu diupgrade lagi secara besar-besaran dan kembali bertanding melawan Kasparov pada Mei 1997. Dalam pertandingan enam babak tersebut Deep Blue menang dengan hasil 3,5- 2,5. Babak terakhirnya berakhir pada 11 Mei. Deep Blue menjadi komputer pertama yang mengalahkan juara dunia bertahan. Komputer ini saat ini sudah "dipensiunkan" dan dipajang di Museum Nasional Sejarah Amerika (National Museum of American History),Amerika Serikat. http://id.wikipedia.org/wiki/Deep_Blue Catur komputer Dari Wikipedia bahasa Indonesia, ensiklopedia bebas Komputer catur dengan layar LCD pada 1990-an Catur komputer adalah arsitektur komputer yang memuat perangkat keras dan perangkat lunak komputer yang mampu bermain caturtanpa kendali manusia. Catur komputer berfungsi sebagai alat hiburan sendiri (yang membolehkan pemain latihan atau hiburan jika lawan manusia tidak ada), sebagai alat bantu kepada analisis catur, untuk pertandingan catur komputer dan penelitian untuk kognisi manusia. Kategori Deep Blue (chess computer) From Wikipedia, the free encyclopedia Deep Blue Deep Blue was a chess-playing computer developed by IBM. On May 11, 1997, the machine, with human intervention between games, won the second six-game match against world champion Garry Kasparov, two to one, with three draws.[1] Kasparov accused IBM of cheating and demanded a rematch. -
Biography Five Related and Significant Publications
GUY BLELLOCH Professor Computer Science Department Carnegie Mellon University Pittsburgh, PA 15213 [email protected], http://www.cs.cmu.edu/~guyb Biography Guy E. Blelloch received his B.S. and B.A. from Swarthmore College in 1983, and his M.S. and PhD from MIT in 1986, and 1988, respectively. Since then he has been on the faculty at Carnegie Mellon University, where he is now an Associate Professor. During the academic year 1997-1998 he was a visiting professor at U.C. Berkeley. He held the Finmeccanica Faculty Chair from 1991–1995 and received an NSF Young Investigator Award in 1992. He has been program chair for the ACM Symposium on Parallel Algorithms and Architectures, program co-chair for the IEEE International Parallel Processing Symposium, is on the editorial board of JACM, and has served on a dozen or so program committees. His research interests are in parallel programming languages and parallel algorithms, and in the interaction of the two. He has developed the NESL programming language under an ARPA contract and an NSF NYI award. His work on parallel algorithms includes work on sorting, computational geometry, and several pointer-based algorithms, including algorithms for list-ranking, set-operations, and graph connectivity. Five Related and Significant Publications 1. Guy Blelloch, Jonathan Hardwick, Gary L. Miller, and Dafna Talmor. Design and Implementation of a Practical Parallel Delaunay Algorithm. Algorithmica, 24(3/4), pp. 243–269, 1999. 2. Guy Blelloch, Phil Gibbons and Yossi Matias. Efficient Scheduling for Languages with Fine-Grained Parallelism. Journal of the ACM, 46(2), pp. -
Paging with Connections: FIFO Strikes Again
Paging with connections: FIFO strikes again Leah Epstein a Yanir Kleiman b Jiˇr´ıSgall c,1 Rob van Stee d,2 aDepartment of Mathematics, University of Haifa, 31905 Haifa, Israel. bThe Academic College of Tel-Aviv Yaffo, Antokolski 4 61161 Tel-Aviv, Israel. cMathematical Institute, AS CR, Zitn´a25,ˇ CZ-11567 Praha 1, Czech Republic, and Dept. of Applied Mathematics, Faculty of Mathematics and Physics, Charles University, Praha. dDepartment of Computer Science, University of Karlsruhe, P.O. Box 6980, D-76128 Karlsruhe, Germany. Tel. nr. +49-721-6086781, Fax +49-721-6083088 Abstract We continue the study of the integrated document and connection caching problem. We focus on the case where the connection cache has a size of one and show that this problem is not equivalent to standard paging, even if there are only two locations for the pages, by giving the first lower bound that is strictly higher than k for this problem. We then give the first upper bound below the trivial value of 2k for this problem. Our upper bound is k + 4ℓ where ℓ is the number of locations where the requested pages in a phase come from. This algorithm groups pages by location. In each phase, it evicts all pages from one location before moving on to the next location. In contrast, we show that the lru algorithm is not better than 2k-competitive. We also examine the resource augmented model and show that the plain fifo algorithm is optimal for the case h = 2 and all k ≥ 2, where h is the size of the offline document cache. -
Deep Thought Wins Fredkin Intermediate Prize Hans Berliner
AI Magazine Volume 10 Number 2 (1989) (© AAAI) CHESS REPORT Deep Thought Wins Fredkin Intermediate Prize Hans Berliner ince May 1988, Deep Thought almost all potential contenders. The S (DT), the creation of a team of two first place finishers drew with students at Carnegie Mellon Universi- each other. Hitech led the field at the ty, has been attracting a lot of notice. halfway point but lost to DT in round In the Fredkin Masters Open, May 3 and threw away a winning position 28–30, DT tied for second in a field of against Fidelity in round four (because over 20 masters and ahead of three of a programming bug). The level of other computers, including Hitech play in this tournament was by far the and Chiptest (the winner of the 1987 best ever in a computer event, and the North American Computer Champi- winners clearly deserved their top onships). In August at the U.S. Open, places. DT scored 8.5, 3.5 to tie for eigh- Ten days later, DT achieved the teenth place with Arnold Denker greatest computer success to date. It among others. Its performance was tied for first with GM Tony Miles in marred by hardware and software the prestigious Software Toolworks bugs. However, DT astounded every- Open in Los Angeles with a score of one by beating International Master 6.5, 1.5. Several GMs played in this (IM) Igor Ivanov, the perennial winner tournament, including former World of the U.S. Grand Prix circuit prize, Champion Mikhail Tal of the USSR. who is generally regarded to be as In the tournament, DT became the strong as the average Grandmaster first computer to beat a GM in a regu- (GM). -
Raluca Budiu
Raluca Budiu 5559 Bartlett St., Apt. B3 Pittsburgh, PA 15217 (412) 422-7214 or (412) 216-4862 [email protected] http://www.cs.cmu.edu/˜ralucav Research Interests Computational models of language, natural language understanding, tutoring systems, educa- tional testing, metaphor comprehension, sentence and discourse processing, learning new word meanings, learning from instruction, knowledge formation Education 2001 Ph.D. in Computer Science. Carnegie Mellon University, Pittsburgh, PA. Supervisor: Prof. John R. Anderson. Ph.D. Thesis: The Role of Background Knowledge in Sentence Processing. This disser- tation describes a computational theory of sentence processing at the semantic level. It offers a unique explanation to behavioral data from a number of domains such as metaphor comprehension, sentence memory and semantic illusions and is validated by comparing the results of its simulation with those produced by human subjects on similar tasks. 1999 M.S. in Computer Science. Carnegie Mellon University, Pittsburgh, PA. 1996 M.S. in Signal Processing. University “Politehnica” of Bucharest, Romania. 1995 B.S. in Computer Science. University “Politehnica” of Bucharest, Romania. Research Experience 2001–2003 Carnegie Mellon University, Pittsburgh, PA. Postdoctoral research associate for Prof. John R. Anderson. Developed INP, a com- putational model of language processing that integrated syntactic and semantic processing. Designed, conducted, and analyzed experiments involving human subjects. 1 Raluca Budiu 2 1996–2001 Carnegie Mellon University, Pittsburgh, PA. Graduate research assistant for Prof. John R. Anderson. Collected behavioral data and developed computational models for learning metaphors and artificial words in context, knowledge transfer in artificial language acquisition, Moses illusion, metaphor comprehension, sentence memory, semantic language processing within the ACT-R framework. -
INSIDE: February 2002 PHYSICS NEWS NEWS Volume 11, No
INSIDE: February 2002 PHYSICS NEWS NEWS Volume 11, No. 2 IN 2001 A Publication of The American Physical Society http://www.aps.org/apsnews Electronic Reminders Biophysics Help Boost Membership, Workshop Planned for Voting Rates Fall 2002 APS membership for fiscal year new members coming in stayed The APS, together with its Di- 2002 is up by almost 500 members roughly the same this year,” she vision of Biological Physics, is compared to the same time last says. “We seem to be doing better organizing a topical conference year. An end-of-year count shows at retaining members once they entitled “Opportunities in Biology that the total number of members join,” something she ascribes to for Physicists,” to be held Sep- now stands at 42,007, compared “increased communication with tember 27-29 2002 in Boston, to 41,570 in fiscal year 2001. Trish members and a great membership Massachusetts. The conference Lettieri, APS Director of Member- staff who are eager to respond to is aimed primarily at graduate ship, attributes the increase in part member inquiries.” students and postdocs who are to a series of electronic renewal Electronic reminder notices reported that response was up 24% August shows sharp spikes coincid- considering moving their areas notices that are sent out to current also proved useful in boosting the over last year, with 23.4% of the ing with electronic reminder of research concentration to members during their renewal number of ballots cast in the an- APS membership voting, compared notices sent to the entire member- biological topics, not at those cycle, and followed up by personal nual APS general election. -
New Paths from Splay to Dynamic Optimality∗
New Paths from Splay to Dynamic Optimality∗ Caleb C. Levyy1 and Robert E. Tarjanz2,3 1Baskin School of Engineering, UC Santa Cruz 2Department of Computer Science, Princeton University 3Intertrust Technologies arXiv:1907.06310v1 [cs.DS] 15 Jul 2019 ∗Research at Princeton University partially supported by an innovation research grant from Princeton and a gift from Microsoft. [email protected] [email protected] 1 Abstract Consider the task of performing a sequence of searches in a binary search tree. After each search, an algorithm is allowed to arbitrarily restructure the tree, at a cost proportional to the amount of restructuring performed. The cost of an execution is the sum of the time spent searching and the time spent optimizing those searches with restructuring operations. This notion was introduced by Sleator and Tarjan in (JACM, 1985), along with an algorithm and a conjecture. The algorithm, Splay, is an elegant procedure for performing adjust- ments while moving searched items to the top of the tree. The conjecture, called dynamic optimality, is that the cost of splaying is always within a constant factor of the optimal algorithm for performing searches. The con- jecture stands to this day. In this work, we attempt to lay the foundations for a proof of the dynamic optimality conjecture. Central to our methods are simulation embeddings and approximate monotonicity. A simulation embedding maps each execution to a list of keys that induces a target algorithm to simulate the execution. Approximately monotone algorithms are those whose cost does not increase by more than a constant factor when keys are removed from the list. -
Results of Acm's Eighteenth Computer Chess
MEETINGREPORT RESULTS OF ACM’S EIGHTEENTH COMPUTER CHESS CHAMPIONSHIP MONTY NEWBORN and DANNY KOPEC CHIPTEST-M, a chess-playing computer program devel- at least one level deeper than its opponents searched oped by a team of three graduate students at Carnegie- and apparently too much of an advantage for any of Mellon University, took first place at ACM’s 18th North them to overcome. The program is only two years old American Computer Chess Championship held at the and has less chess knowledge than its main rivals, but ACM/IEEE-CS Fall Joint Computer Conference in Dal- the enormous tree that it searches more than makes up las, Texas last October. With the strongest field ever for these shortcomings. assembled for a computer chess event, including cur- Hsu expects to improve the program over the coming rent World Champion CRAY BLITZ and former World year by introducing parallelism. His chip can be repli- Champion BELLE, CHIPTEST-M overpowered the field cated, and with the talent that has created the current of 12 with a perfect 4-0 performance to capture the version, a parallel version can be anticipated which $2000 first place prize. En route to winning the champi- will be significantly stronger. The program was as- onship, the program defeated CRAY BLITZ in the third signed a 2584 performance rating at the Dallas event round and then routinely disposed of SUN PHOENIX in by Ken Thompson’s rating program. This salys that the final fourth round. CRAY BLITZ finished in second CHIPTEST-M was playing at the level of a Grandmaster place, while SUN PHOENIX settled for third. -
Contents U U U
Contents u u u ACM Awards Reception and Banquet, June 2018 .................................................. 2 Introduction ......................................................................................................................... 3 A.M. Turing Award .............................................................................................................. 4 ACM Prize in Computing ................................................................................................. 5 ACM Charles P. “Chuck” Thacker Breakthrough in Computing Award ............. 6 ACM – AAAI Allen Newell Award .................................................................................. 7 Software System Award ................................................................................................... 8 Grace Murray Hopper Award ......................................................................................... 9 Paris Kanellakis Theory and Practice Award ...........................................................10 Karl V. Karlstrom Outstanding Educator Award .....................................................11 Eugene L. Lawler Award for Humanitarian Contributions within Computer Science and Informatics ..........................................................12 Distinguished Service Award .......................................................................................13 ACM Athena Lecturer Award ........................................................................................14 Outstanding Contribution -
The Design and Implementation of an Adaptive Chess Game
California State University, San Bernardino CSUSB ScholarWorks Electronic Theses, Projects, and Dissertations Office of aduateGr Studies 9-2015 THE DESIGN AND IMPLEMENTATION OF AN ADAPTIVE CHESS GAME Mehdi Peiravi mehdi peiravi Follow this and additional works at: https://scholarworks.lib.csusb.edu/etd Part of the Robotics Commons Recommended Citation Peiravi, Mehdi, "THE DESIGN AND IMPLEMENTATION OF AN ADAPTIVE CHESS GAME" (2015). Electronic Theses, Projects, and Dissertations. 228. https://scholarworks.lib.csusb.edu/etd/228 This Project is brought to you for free and open access by the Office of aduateGr Studies at CSUSB ScholarWorks. It has been accepted for inclusion in Electronic Theses, Projects, and Dissertations by an authorized administrator of CSUSB ScholarWorks. For more information, please contact [email protected]. THE DESIGN AND IMPLEMENTATION OF AN ADAPTIVE CHESS GAME A Project Presented to the Faculty of California State University, San Bernardino In Partial Fulfillment of the Requirements for the Degree Master of Science in Computer Science by Mehdi Peiravi September 2015 THE DESIGN AND IMPLEMENTATION OF AN ADAPTIVE CHESS GAME A Project Presented to the Faculty of California State University, San Bernardino by Mehdi Peiravi September 2015 Approved by: Haiyan Qiao, Committee Chair, Computer Science Kerstin Voigt, Committee Member Ernesto Gomez, Committee Member © 2015 Mehdi Peiravi ABSTRACT In recent years, computer games have become a common form of entertainment. Fast advancement in computer technology and internet speed have helped entertainment software developers to create graphical games that keep a variety of players’ interest. The emergence of artificial intelligence systems has evolved computer gaming technology in new and profound ways. -
Artificial Intelligence and the Making of IBM's Deep Blue
The Deep Blue Chess Computer Randy Moulic, PhD(EE), IEEE Life Fellow Associate Professor, Computer Science and Engineering University of Alaska-Anchorage June 26th, 2014 For 1000s of Years Man Built Machines to Enhance and Extend Human Capabilities in the Physical World Man’s intelligence, creativity and autonomous nature have been at the core of these advancements “Machines for the Mind” Computers Enrich Our Daily Lives, and Free Our Minds by Handling Tedious, Repetitious Tasks ….. can computers exhibit such human-like intelligence, creativity and autonomous behaviors? Chess: an Olympic Sport for the Mind • Critical thinking • Comprehension • Creativity • Analysis • Knowledge and memory Winning at chess; being the world champion has been a measure of a highly developed, creative mind ! Could a machine beat the best human chess player in the world? …a Machine that Appears to Think, Solve and Create, Like the Human Mind ? The Turk (1770 – 1854) Charles Babbage (1864) • In 1864, Charles Babbage described how chess could be programmed on his unique, special purpose, Analytical Engine • Babbage was never able to raise funding to build the Analytical Engine Oh, by the way it was a “computer” design Claude E. Shannon Computational Requirements of Chess 3 major computational tasks are necessary in a computer chess “engine”: • Move generation of all possible legal moves • “Move tree” search • Evaluation Computational Requirements of Chess Move option #30 Move option #3 Move option #2 Move option #1 ~30 possible moves per player per ply, a depth of 12 ply requires the generation, searching and evaluation, of 4.7 x 10 20 positions !! “Move tree” A Deeper Look Into The Computational Tasks Simple “Material” Based Evaluation • Evaluation function for a move based on C. -
The K-Server Problem
The k-server problem Elias Koutsoupias∗ April 13, 2009 Abstract The k-server problem is perhaps the most influential online problem: natural, crisp, with a surprising technical depth that manifests the richness of competitive analysis. The k-server conjecture, which was posed more that two decades ago when the problem was first studied within the competitive analysis framework, is still open and has been a major driving force for the development of the area online algorithms. This article surveys some major results for the k-server. 1 Introduction The k-server problem in a metric space (or weighted graph) is the problem of moving around efficiently k servers to service requests that appear online at the points of the metric space. The k servers start at a fixed set of k points which we call the initial configuration. Then in each time step a request appears at some point of the metric space and some server has to move to that point to service the request. We assume that the requests appear sequentially and that a new request appears only after the current request has been serviced. The goal is to minimize the total distance traveled by the servers. More formally, the definition of the problem is as follows: Let M be a metric space and let d(a1,a2) denote the distance in M of points a1 and a2. The distance d is nonnegative, symmetric, and satisfies the triangle inequality. For simplicity, we allow distinct points to be at distance 0, or more formally, M is a pseudometric rather than metric.