This is a call for bids to host the Twelfth International Conference on Autonomous Agents and Multiagent Systems (AAMAS) in 2013. Bids will be considered from all geographical regions; however, for the 2013 conference, we particularly encourage bids from the Americas.
Bids are sought from volunteers from the scientific community, though they may be supported by paid meeting professionals.
All correspondence regarding bids should be directed by email to the IFAAMAS Conference Committee Chair (Munindar P. Singh, singh@ncsu.edu) and Chair Elect (Onn Shehory, ONN@il.ibm.com).
Bids should be made by individuals or small groups, with the backing of a host institution, typically a university or research center. Groups or individuals who are planning to submit a bid should notify Drs. Singh and Shehory of their intention as soon as possible.
Now: Expression of interest and queries
November 17, 2010: Submission of final bid
November 18, 2010-February 28, 2011: Potential discussions with bidders; internal discussions in the IFAAMAS Board
According to a recent post in the Microsoft Careers JobsBlog the top three hottest new majors for a career in technology are
Data Mining/Machine Learning/AI/Natural Language Processing
Business Intelligence/Competitive Intelligence
Analytics/Statistics, specifically Web Analytics, A/B Testing and
statistical analysis
Happily these are all strengths of the IT programs at UMBC. In fact, we have placed a large number of graduates at leading edge technology companies in the past few years, including Microsoft, Google, Amazon, IBM, and Yahoo.
The University of Waterloo’s computer science club is holding another Google-sponsored AI Challenge this Fall. The task is to write a program to compete in a Planet Wars tournament. Your goal is to conquer all the planets in your corner of space or eliminate all of your opponents ships. Starter programs are available in Python, Java, C# and C++ and support for Common Lisp, Haskell, Ruby and Perl is under development. The contest starts on September 10th and ends on November 27th. Sounds like fun!
Planet Wars is inspired by Galcon iPhone and desktop strategy game. Here’s a Planet Wars game in action.
The Maryland Clean Energy Technology Incubator (CETI) at bwtech@UMBC will host a seminar series this Fall with focus on the Smart Grid. The series will discuss the issues and opportunities and speculate on expected business opportunities in this major restructuring of the electric grid. Huge investments (tens of billions of dollars) are committed to the Smart Grid for the coming decade.
About six seminars are planned for Fall 2010 to be held (mostly) on Wednesdays from 4-6pm and UMBC faculty, staff and students are encouraged to participate. They will include a ~45 minute presentation followed by a lively discussion and opportunity to socialize and enjoy light refreshments.
The first speaker, Peter Kelly-Detwiler leads a group at Constellation Energy that is developing new methods for data analysis and presentation. He is an “entrepreneur” within Constellation with 20 years of experience in the energy field and he has a perspective on the Smart Grid like few others.
A smart grid perspective: finding value in the collision of energy and information
Peter Kelly-Detwiler, Constellation Energy
4-6pm Wednesday, 8 September 2010
2nd floor Courtyard Conference Room UMBC Tech Center
Many people have heard of the term “smart grid” and there are many varying interpretations of what it means. But everybody can agree on three things:
It involves increased and timely access to information
There’s money in it
It will create new and unforeseen technologies and entrepreneurial opportunities
The discussion will center around why smart grid is needed, how an energy provider views the challenges and opportunities, the forces we see gathering on the horizon, and how Constellation Energy is responding. Issues related to power grid economics, volatility, risk management, and customer elasticities and perspectives will be addressed.
Peter Kelly-Detwiler is Senior Vice President of Energy Technology Services for Constellation NewEnergy, Inc., a subsidiary of Constellation Energy Group. He and his company-wide team oversee the integration of efficiency technologies and applications that help customers better manage their total energy bills and create optimal energy solutions. Peter has 20 years of experience in the energy industry. His accomplishments include managing the development of energy efficiency projects and reviewing economic impact of energy products.
Please RSVP to Bjorn Frogner (bjorn.frogner@umbc.edu), the CETI Entrepreneur in Residence, if you plan to attend.
Using a combination of mathematical tricks, good programming and 35 CPU-years on Google’s servers, a group of researchers have proved that every position of Rubik’s Cube can be solved in 20 moves or less. The group consists of Kent State mathematician Morley Davidson, Google engineer John Dethridge, math teacher Herbert Kociemba, and programmer Tomas Rokicki.
This is an amazing result and a testament to more than 30 years of work on the problem. The Cube was invented in 1974 and almost immediately the subject for programs to solve it. In 1981, Morwen Thistlethwaite proved that any configuration could be solved in no more than 52 moves. Periodically, tighter upper bounds for the maximum solution length were found. This result ends the quest — there are some configurations (about 300M) that require 20 moves to solve and there are none that require more than 20 moves.
In their own words, here’s how the group solved all 43,252,003,274,489,856,000 Cube positions:
We partitioned the positions into 2,217,093,120 sets of 19,508,428,800 positions each.
We reduced the count of sets we needed to solve to 55,882,296 using symmetry and set covering.
We did not find optimal solutions to each position, but instead only solutions of length 20 or less.
We wrote a program that solved a single set in about 20 seconds.
We used about 35 CPU years to find solutions to all of the positions in each of the 55,882,296 sets.
This reminds me of the first program I wrote for my own enjoyment, which used brute force to find all solutions to Piet Hein’s Soma Cube. In 1969 I had a summer job as the night operator for an IBM 360 and I would turn off the clock to run my program so that the management wouldn’t know how much computer time I was consuming.
See this BBC story more more information on this amazing result.
The W3C has published a second working draft of EmotionML, or the emotion markup language, Here’s how it’s described.
As the web is becoming ubiquitous, interactive, and multimodal, technology needs to deal increasingly with human factors, including emotions. The present draft specification of Emotion Markup Language 1.0 aims to strike a balance between practical applicability and scientific well-foundedness. The language is conceived as a “plug-in” language suitable for use in three different areas: (1) manual annotation of data; (2) automatic recognition of emotion-related states from user behavior; and (3) generation of emotion-related system behavior.
Unfortunately EmotionML is not built on RDF. If it were, I would have marked up this post in RDFa using it!
The working draft identifies concrete examples where EmotionML might be useful including as a markup or representation for systems that do opinion mining, sentiment analysis, affect monitoring, and emotion recognition. A list of 39 individual use cases for EmotionML are given in an appendix.
EmotionML markup explicitly refers to one or more separate vocabularies used for representing emotion-related states. However, the group has defined some default vocabularies that can be used. An example is the Ekman “big six” basic emotions (anger, disgust, fear, happiness, sadness, and surprised). Another is the a set of appraisal terms defined by Ortony et al. (desirability, praiseworthiness, appealingness,, desirability-for-other, deservingness, liking, likelihood, effort, realization, strength-of-identification, expectation-of-deviation and familiarity)
Here’s an example from the working draft where a static image is annotated with several emotion categories with different intensities.
Here’s a great resource if you want to come up to speed on ontologies and their importance today.
Professor Barry Smith of the University at Buffalo held a two-day course, An Introduction to Ontology: From Aristotle to the Universal Core, in 2009, to introduce ontologies and their applications to both philosophers and computer scientists. It consisted of of eight lectures for which slides and downloadable videos are available. Paul Alexander has also made the videos available in streaming form here if you want to view them without downloading.
The lectures are all either 60 or 90 minutes. Here are links to the streaming videos, thanks to Paul Alexander:
Training Examples QA is a site created by Joseph Turian where “data geeks ask and answer questions on machine learning, natural language processing, artificial intelligence, text analysis, information retrieval, search, data mining, statistical modeling, and data visualization!”
It’s a close knock off of the popular stack overflow site and appears to be very well done.
If it catches on in the relevant research communities, it could be a very useful resource. (via LingPipe blog)
Journal of Web Semantics Special Issue on Using Provenance in the Semantic Web
Editors: Yolanda Gil, University of Southern California’s Information Sciences Institute and Paul Groth, Free University of Amsterdam
The Web is a decentralized system full of information provided by diverse open sources of varying quality. For any given question there will be a multitude of answers offered, raising the need for assessing their relative value and for making decisions about what sources to trust. In order to make effective use of the Web, we routinely evaluate the information we get, the sources that provided it, and the processes that produced it. A trust layer was always present in the Web architecture, and Berners-Lee envisioned an “oh-yeah?” button in the browser to check the sources of an assertion. The Semantic Web raises these questions in the context of automated applications (e.g. reasoners, aggregators, or agents), whether trying to answer questions using the Linked Data cloud, use a mashup appropriately or determine trust on a social network. Therefore, provenance is an important aspect of the Web that becomes crucial in Semantic Web research.
This special issue on Using Provenance in the Semantic Web of the Journal of Web Semantics aims to collect representative research in handling provenance while using and reasoning about information and resources on the web. Provenance has been addressed in a variety of areas in computer science targeting specific contexts, such as databases and scientific workflows. Provenance is important in a variety of contexts, including open science, open government, and intellectual property and copyright. Provenance requirements must be understood for specific kinds of Web resources, such as documents, services, ontologies, workflows, and datasets.
We seek high quality submissions that describe recent projects, articulate research challenges, or put forward synergistic perspectives on provenance. We solicit submissions that advance the Semantic Web through exploiting provenance, addressing research issues including:
representing provenance
relating provenance to the underlying data and information
managing provenance in a distributed web
reasoning about trust based on provenance
handling incomplete provenance
taking advantage of the web’s structure for provenance
Submissions may focus on uses of provenance in the Semantic Web for:
linked data
social networking
data integration
inference from diverse sources
trust and proof
Papers may also focus on application areas, highlighting the challenges and benefits of using provenance:
provenance in open science
provenance in open government
provenance in copyright and intellectual property for documents
provenance in web publishing
Important Dates
We will aim at an efficient publication cycle in order to guarantee prompt availability of the published results. We will review papers on a rolling basis as they are submitted and explicitly encourage submissions well before the submission deadline. Submit papers online at the journal’s Elsevier Web site.
Submission deadline: 5 September20 September 2010
Author notification: 15 December 2010
Revisions submitted: 1 February 2010
Final decisions: 15 March 2011
Publication: 1 April 2011
Submission guidelines
The Journal of Web Semantics solicits original scientific contributions of high quality. Following the overall mission of the journal, we emphasize the publication of papers that combine theories, methods and experiments from different subject areas in order to deliver innovative semantic methods and applications. The publication of large-scale experiments and their analysis is also encouraged to clearly illustrate scenarios and methods that introduce semantics into existing Web interfaces, contents and services. Submission of your manuscript is welcome provided that it, or any translation of it, has not been copyrighted or published and is not being submitted for publication elsewhere. Upon acceptance of an article, the author(s) will be asked to transfer copyright of the article to the publisher. This transfer will ensure the widest possible dissemination of information. Manuscripts should be prepared for publication in accordance with instructions given in the “Guide for Authors” (available from the publisher), details can be found online. The submission and review process will be carried out using Elsevier’s Web-based EES system. Final decisions of accepted papers will be approved by an editor in chief.
About the Journal of Web Semantics
The Journal of Web Semantics is published by Elsevier since 2003. It is an interdisciplinary journal based on research and applications of various subject areas that contribute to the development of a knowledge-intensive and intelligent service Web. These areas include: knowledge technologies, ontology, agents, databases and the semantic grid, obviously disciplines like information retrieval, language technology, human-computer interaction and knowledge discovery are of major relevance as well. All aspects of the Semantic Web development are covered. The current Editors-in-Chief are Tim Finin, Riichiro Mizoguchi and Steffen Staab. For all editors information, see our site.
The Journal of Web Semantics offers to its authors and readers:
Professional support with publishing by Elsevier staff
Indexed by Thomson-Reuters web of science
Impact factor 3.41: the third highest out of 92 titles in Thomson-Reuters’ category “Computer Science, Information Systems
Kaggle is a site for data-related competitions in machine learning, statistics and econometrics. Companies, researchers, government and other organizations will be able to post their modeling problems and invite researchers to compete to produce the best solutions. The Kaggle demo site currently has three example competitions to illustrate how it will work and expects to host the first real one in March. Kaggle’s competition hosting service will be free, but the site says that it plans to “offer paid-for services in addition to its free competition hosting.”
The Journal of Web Semantics has announced two new special issues. Heiner Stuckenschmidt and Jeff Heflin are editing a special issue on web-scale semantic information processing with a deadline of 1 July 2010 for submissions. Grigoris Antoniou, Mathieu d’Aquin and Jeff Z. Pan are editing a special issue on semantic web dynamics with submissions due 31 May 2010.
The new Scientist has an article, Learning to love to hate robots, on recent research on how humans and robots interact and ways to improve the relationships. The most popular robot in such “opposite relationships” is, of course, the little Roomba. Searching for roomba on Flickr produces more than 5000 pictures taken by their human friends.
“A six-month study of how Roomba affected households, conducted by Ja-Young Sung at the Georgia Institute of Technology in Atlanta, backs up that finding. “Some people saw it as a lifetime partner – they had a real emotional attachment to it.” Even those who returned to their previous cleaning routine didn’t blame the robot, instead saying it was their routine that was at fault.”
The little guy is pretty savvy — it knows how how to get ahead even if it doesn’t have the fastest cores on the block: manage expectations.
“One study by Jodi Forlizzi at Carnegie Mellon University in Pittsburgh, Pennsylvania, highlights how popular culture can affect a robot’s reception. People she introduced to Roomba, a robotic vacuum cleaner made by iRobot of Bedford, Massachusetts, compared it with their knowledge of robots that explore Mars, forming low expectations of Roomba’s abilities. But making a bad first impression seemed to help Roomba; it invariably surpassed expectations, helping people bond with their machine.”
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