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Government
Knowware: the third star after Hardware and Software
This book proposes to separate knowledge from software and to make it a commodity that is called knowware. The architecture, representation and function of Knowware are discussed. The principles of knowware engineering and its three life cycle models: furnace model, crystallization model and spiral model are proposed and analyzed. Techniques of software/knowware co-engineering are introduced. A software component whose knowledge is replaced by knowware is called mixware. An object and component oriented development schema of mixware is introduced. In particular, the tower model and ladder model for mixware development are proposed and discussed. Finally, knowledge service and knowware based Web service are introduced and compared with Web service. In summary, knowware, software and hardware should be considered as three equally important underpinnings of IT industry. Ruqian Lu is a professor of computer science of the Institute of Mathematics, Academy of Mathematics and System Sciences. He is a fellow of Chinese Academy of Sciences. His research interests include artificial intelligence, knowledge engineering and knowledge based software engineering. He has published more than 100 papers and 10 books. He has won two first class awards from the Academia Sinica and a National second class prize from the Ministry of Science and Technology. He has also won the sixth Hua Loo-keng Mathematics Prize.
Translating OWL and Semantic Web Rules into Prolog: Moving Toward Description Logic Programs
Samuel, Ken, Obrst, Leo, Stoutenberg, Suzette, Fox, Karen, Franklin, Paul, Johnson, Adrian, Laskey, Ken, Nichols, Deborah, Lopez, Steve, Peterson, Jason
To appear in Theory and Practice of Logic Programming (TPLP), 2008. We are researching the interaction between the rule and the ontology layers of the Semantic Web, by comparing two options: 1) using OWL and its rule extension SWRL to develop an integrated ontology/rule language, and 2) layering rules on top of an ontology with RuleML and OWL. Toward this end, we are developing the SWORIER system, which enables efficient automated reasoning on ontologies and rules, by translating all of them into Prolog and adding a set of general rules that properly capture the semantics of OWL. We have also enabled the user to make dynamic changes on the fly, at run time. This work addresses several of the concerns expressed in previous work, such as negation, complementary classes, disjunctive heads, and cardinality, and it discusses alternative approaches for dealing with inconsistencies in the knowledge base. In addition, for efficiency, we implemented techniques called extensionalization, avoiding reanalysis, and code minimization.
The Second International Conference on Human-Robot Interaction
Schultz, Alan C., Breazeal, Cynthia, Fong, Terry, Kiesler, Sara
Hackman delivered a talk entitled "Humans, Robots, and Teams" that leveraged work in The conference's outstanding paper award went to "Humanoid Robots as a Passive-Social Medium: A Field Experiment at a Train Station" by Kotaro The best student paper award went to Guy Hoffman and Cynthia Breazeal for their paper, titled "Effects of Anticipatory HRI-2007 was the second step "Speed Adaptation for a Robot Walking Spurred by included teamwork, social robotics, momentum has been built for HRI-advances in robotics technologies and adaptation, observation and metrics, 2008, which will be held in Amsterdam, communications, many researchers attention, user experience, and The Netherlands, March 12-15, are studying how to use these field testing. The 21st International FLAIRS Conference (FLAIRS-21) will be held May 15 - 17, 2008 at the Grand Bay Miami Hotel in the village of Coconut Grove, Miami, Florida, USA. The conference hotel is on the waterfront of Biscayne Bay close to downtown Miami and South Beach. FLAIRS-21 will feature technical papers, special tracks, and General Chair invited speakers on artificial intelligence. Architectures: Agents and distributed AI, Intelligent user interfaces, Natural lane@ict.usc.edu
AAAI News
Symposia will be limited to between forty and sixty participants. Each participant will be expected to attend a single symposium. In addition to invited participants, a limited number of other interested parties will be allowed to register in each symposium on a first-come, first-served basis. Working notes will be prepared and distributed to participants in each symposium, but will not otherwise be available unless published as an AAAI Technical Report or edited collection. The final deadline for registration is October 12, 2007. For registration information, please contact AAAI at fss07@aaai.org or visit AAAI's web site (www.aaai.org/Symposia/Fall/fss07.
AI in the News
But less impressive are our and related AI TOPICS pages--at www. of it. July 10, 2007 task of fruit picking that currently employs not imply any endorsement whatsoever. Whether hypnotized by computer the migrant labor force. Farmers faster than the eye can scan them. Dow or console, players age 8 to 34 spend are'very, very nervous about the availability Jones and Reuters, the news providers, more time at this today than watching TV, and cost of labor in the near future,' says now offer electronically'tagged' news according to Nielsen. 'Most grew up addicted to also hopes to use algorithms to comb News.
Learning Probabilistic Models of Word Sense Disambiguation
This dissertation presents several new methods of supervised and unsupervised learning of word sense disambiguation models. The supervised methods focus on performing model searches through a space of probabilistic models, and the unsupervised methods rely on the use of Gibbs Sampling and the Expectation Maximization (EM) algorithm. In both the supervised and unsupervised case, the Naive Bayesian model is found to perform well. An explanation for this success is presented in terms of learning rates and bias-variance decompositions.
Practical Approach to Knowledge-based Question Answering with Natural Language Understanding and Advanced Reasoning
This research hypothesized that a practical approach in the form of a solution framework known as Natural Language Understanding and Reasoning for Intelligence (NaLURI), which combines full-discourse natural language understanding, powerful representation formalism capable of exploiting ontological information and reasoning approach with advanced features, will solve the following problems without compromising practicality factors: 1) restriction on the nature of question and response, and 2) limitation to scale across domains and to real-life natural language text.
Clusters, Graphs, and Networks for Analysing Internet-Web-Supported Communication within a Virtual Community
The proposal is to use clusters, graphs and networks as models in order to analyse the Web structure. Clusters, graphs and networks provide knowledge representation and organization. Clusters were generated by co-site analysis. The sample is a set of academic Web sites from the countries belonging to the European Union. These clusters are here revisited from the point of view of graph theory and social network analysis. This is a quantitative and structural analysis. In fact, the Internet is a computer network that connects people and organizations. Thus we may consider it to be a social network. The set of Web academic sites represents an empirical social network, and is viewed as a virtual community. The network structural properties are here analysed applying together cluster analysis, graph theory and social network analysis.
Model Selection Through Sparse Maximum Likelihood Estimation
Banerjee, Onureena, Ghaoui, Laurent El, d'Aspremont, Alexandre
We consider the problem of estimating the parameters of a Gaussian or binary distribution in such a way that the resulting undirected graphical model is sparse. Our approach is to solve a maximum likelihood problem with an added l_1-norm penalty term. The problem as formulated is convex but the memory requirements and complexity of existing interior point methods are prohibitive for problems with more than tens of nodes. We present two new algorithms for solving problems with at least a thousand nodes in the Gaussian case. Our first algorithm uses block coordinate descent, and can be interpreted as recursive l_1-norm penalized regression. Our second algorithm, based on Nesterov's first order method, yields a complexity estimate with a better dependence on problem size than existing interior point methods. Using a log determinant relaxation of the log partition function (Wainwright & Jordan (2006)), we show that these same algorithms can be used to solve an approximate sparse maximum likelihood problem for the binary case. We test our algorithms on synthetic data, as well as on gene expression and senate voting records data.
AI in the News
'We should be worried, for aaai.org/aitopics/ We are Please note that: (1) an excerpt may not my understanding, I visited USC's'We need to tell the the fact that an item has been selected does University of Massachusetts in Amherst, Robot Wars -- An Attempt to Build an with many of the programs in the omy -- that prompted interest in the technology, Ethical Robotic Soldier. 'We are Technology, in Atlanta, is developing a set those tested uses the sort of artificial intelligence studying the application of the RAHS concepts of rules of engagement for battlefield technology that encourages highlevel and tools to the social, and economic robots to ensure that their use of lethal interactivity.... Call me an industry and financial domains,' Nathan wrote force follows the rules of ethics. In other cheerleader, but what I see at [William in an email interview." Kim conscience.... His approach is to create suggests that computers are already helping Yoon-mi. April 28, 2007 what he calls a'multidimensional mathematical students learn and will become increasingly (www.koreaherald.co.kr). "To literally live decision space of possible behavior important year by year." with robots, that are highly likely to become actions'.... Arkin has started to survey policy Search Engine Spawned from Antiterrorism more intelligent and physically closer makers, the public, researchers and military Efforts Finds Place in Business. "Artificial-intelligence-based that will prevent robots from doing harm Computer Science Takes Steps to Bring search technology to people, and block humans from taking Women to the Fold.