• Also see: Magenta Deploys its Multi-Agent Technology to Optimize One of the World's Largest Oil Tanker Fleets. PRNewswire / available from WQAD (August 13, 2004). "[W]hen a new cargo is offered, agents are created within the database that contains all the data about the cargo - for example freight rates, size and type of cargo, as well as load and discharge ports. The agents then negotiate within the virtual market to decide the optimum vessel for the cargo, based on TI's fleet strategy. The agents do this by competing to find the best solution between supply and demand by comparing alternative routes, vessels, ports, costs, freight rates, fuel for propulsion, speed, distance and even positions of the vessels. This data and the defining concepts upon which the agents base their decisions are stored within the knowledge database, known as the Ontology. Unlike other systems, the agents are also able to resolve conflicts as they are not bound by rigid rules and are able to work around problems."

July 28, 2004: Amplified Intelligence - The AI Problem. Interview with Ken Ford. Astrobiology Magazine. "Astrobiology Magazine (AM): The IMHC [Interdisciplinary Study of Human & Machine Cognition] research agenda broadly seems to cover robotics, cognition and simulations. Are there parts of machine intelligence that your research institute doesn't cover today, but that you see as growth areas? Ken Ford (KF): Don't forget that second letter is 'H'. Although a lot of our research could be categorized as AI, and five of our researchers are AAAI (American Association for Artificial Intelligence) Fellows, IHMC is not a traditional machine intelligence laboratory. The focus and theme of our research is what has become known as human-centered computing which, in a nutshell, is about fitting technology to people instead of fitting people to technology. The human is part of the system, and it is the performance of the whole system, including the human, that we are interested in. This requires that machines should be designed to fit us physically, cognitively, and perhaps even socially. We think of AI as meaning 'Amplified Intelligence.' The interesting thing is that many traditional AI technologies in fact are being used in just this way. We like to refer to it as building cognitive prostheses, computational systems that leverage and extend human intellectual capacities, just as eyeglasses are a kind of ocular prosthesis. Building cognitive prostheses is fundamentally different from AI's traditional Turing Test ambitions -- it doesn't set out to imitate human abilities, but to extend them. ... AM: In your opinion, how well do the machine intelligence problems (like navigation, data-mining, or simulations with agents) map to the basic computer science [CS] problem of efficient 'search'? KF: Wow, efficient search is a 'basic computer science problem'? Not long ago, search was being suggested as a defining characteristic of AI to distinguish it from 'mainstream' CS. But to return to the question: search is certainly a central technique in AI, but the search spaces arising in AI are often impossibly huge, and a more interesting aspect is not so much how to search them efficiently as how to re-cast problems so that the search space itself is reduced in size. Searching is what you do when you can't think of anything smarter."
>>> Interfaces, Search, Robots, Space Exploration, Data Mining, Household Appliances, Interviews, AI Overview, Applications, Reasoning, Machine Learning, Turing Test

July 14, 2004: Attack of the killer vacuum cleaners. By Charles Arthur. The Belfast Telegraph Digital. "Things are about to happen with robots, because the element they need to make them truly useful - the software, which needs to be able to adapt to a wide range of situations - is getting cheaper all the time. Future Horizons, a semiconductor analyst based in Kent, forecasts that by 2010 there will be 55.5 million robots, in a world market worth £30bn - up from £2.4bn last year. 'The electronics industry is on the cusp of a robotics wave, a period in which applications are aimed at labour-saving and extending human skills,' it reports. Of those, it says that 39 million will be domestic robots, and 10.5 million 'domestic intelligent service' robots. That is because there's a growing need for robots to help the elderly and handicapped. ... But the real explosion in robotics is coming among the 'immobots' - or, more simply, just 'bots'. These are bits of software that are incorporated into larger objects, and that remove a lot of the strain of having to decide what to do next. We're getting glimpses of how good these could be at present: the tiny number of Britons with a TiVo personal video recorder have something that decides, based on the programmes they choose to record, what other programmes they might like to see, and records those, too. ... The reason why we can't yet declare 'The Year of the Robot', however, is that researchers are still fundamentally split about how robots should behave and learn. One group favours the 'top-down' approach, in which all the behaviour of the robot is mapped out, and its software is written to fill out that behaviour. The Roomba vacuum cleaner is a classic example.... The alternative is something assembled from smaller, self-contained units, which creates a gestalt of behaviour based on that. Thus the system that controls the legs learns to 'walk' independently.... Sony's Aibo draws on a form of this....
>>> Robots, Science Fiction, Agents, Systems, Assisitive Technologies, Household Appliances, Industry Statistics, Applications, Reasoning, Machine Learning

July 4, 2004: His quest - Do Disney in a day. By Larry Bleiberg. The Dallas Morning News / available from Mickey News. "Rich Vosburgh worked out hard, spending four months with a personal trainer. He scrutinized maps and a detailed timetable. He even deployed a secret weapon: artificial-intelligence research to chart a course through death-defying drops, torrents of water and fiery heat.And when this Texas adventurer clambered out of a floating log a year ago, he had reached his holy grail: visiting - in a single day - each of the 41 operating rides, attractions and shows at the Everest of theme parks, Walt Disney World's Magic Kingdom. His time: a record 10 hours, 40 minutes. ... At heart, the challenge is an enduring and perplexing quandary: What's the most efficient way to route someone to multiple places, taking into account constantly changing conditions? Logistics and timing Mathematicians call it the Time Dependent Traveling Salesman Problem. The answer could help fighter-jet pilots chart bombing targets or freight companies schedule package deliveries."
>>> Traveling Salesperson Problem, Planning and Scheduling, Search, Genetic Algorithms, Machine Learning, Reasoning, Transportation, Applications, Games & Puzzles

June 24, 2004: Informed decisions - CHEO team tests artificial intelligence in neo-natal unit. By Andrew Mayeda. Ottawa Citizen (subscription required). "When a baby is born prematurely, parents must often make a heartbreaking decision of whether to continue care or to simply let go. While that decision will never be easy, a pair of Ottawa researchers have developed artificial-intelligent tools that could at least make it more informed. The result is a software system [Parents Assisting Decision Support] that lets parents know their child's chances of survival, and allows them to weigh the pros and cons of treatment options while consulting their doctor or nurse. ... PADS, as it is called for short, is the brainchild of Dr. Robin Walker and Monique Frize, who have worked together for more than a decade."
>>> Case-Based Reasoning, Neural Networks, Medicine, Applications, Reasoning, Machine Learning

June 10, 2004: Fuzzy logic and neural nets: still viable after all these years? Though no longer headliners, fuzzy logic and neural networks are options in tackling challenging applications. By Graham Prophet. EDN Magazine. "[B]oth still have their place in your engineering tool kit. The two techniques are essentially unrelated, except that they both provide control methodologies to handle highly nonlinear or poorly specified problems, they both came to some prominence at about the same time, and they both faded from view in much the same way. Both neural networks and fuzzy logic aspire to allow electronic systems, built with familiar circuit techniques or employing conventional computing technologies, to attack certain problems in a way that mimics human responses and abilities. ... One of the intimidating aspects of fuzzy logic is the name itself, which has connotations of imprecision. On the contrary, however, fuzzy logic is capable of precise responses. It allows systems built around Boolean logic, handling binary values, to work with imprecisely defined values that you might express verbally as 'more,' 'less,' 'high,' 'low,' and so on. ... Neural networks, unlike fuzzy logic, seek to reproduce the versatility of the human brain in recognizing the end-to-end, input-to-output behavior of a system without understanding all the processes taking place within it. Taking as a fundamental model the interconnections of nervous systems within the brain -- neurons and synapses -- neural networks have the attributes of memory and learning. ... What happens to the expertise built up in neural and fuzzy techniques from their first flush of popularity? If you set about tracking down some of the pioneering companies from as much as a decade ago, you'd find that, although many no longer exist, some have transformed themselves into software-design and consultancy operations. These businesses are applying the same neural and fuzzy techniques but mainly in software simulation running on conventional computers, in areas such as financial modeling, financial services, and data mining."
>>> Fuzzy Logic, Neural Networks, Applications, Banking, Finance & Investing, Data Mining, Reasoning, Machine Learning

June 8, 2004: UCSC man's work earns top award. By David L. Beck. Mercury News (no fee reg. req'd.). "[T]he Association for Computing Machinery honored Santa Cruz's David Haussler on Saturday night at New York's Plaza Hotel.... A mathematician whose contributions to biology are incalculable, Haussler is being given the Allen Newell Award, named for a pioneer in artificial intelligence. ... 'By focusing on scientific interactions between computer scientists and molecular biologists,' the Newell Award announcement noted, 'Dr. Haussler has played a leading role in developing the new field of computational biology.' ... What Haussler and his team at UCSC did was to write computer programs that would take all that DNA -- billions and billions of base pairs, because redundancy is crucial to Haussler's 'probabilistic' approach -- and put them in the right order. Result: the human genome. Some call it a blueprint. Haussler calls it a recipe. ... Haussler shares the Newell Award with Judea Pearl, director of the Cognitive Systems Laboratory at UCLA, whose ideas 'have revolutionized the understanding of causality in statistics, psychology, medicine and the social sciences.'"
>>> Bioinformatics, Reasoning, Applications

May 21, 2004: Supply chain by numbers - Complex mathematics helps business managers think outside the box. By Ephraim Schwartz. InfoWorld. "Long the exclusive domain of AI (artificial intelligence) research, statistical probability analysis got its real start during World War II, when military intelligence wanted a way to predict possible outcomes. Throughout the 1950s, the field was continued by mathematicians such as John Nash, and now this complex discipline is becoming the stuff of ordinary business applications. From a common-sense point of view, the way statistical analysis works seems illogical. The more complex a data set becomes, for instance, the easier it is to make predictions. For example, take NLU (natural language understanding) research. ... NLU program designers input millions of sentences into their software. So, statistically, they know that there might be a 90-percent chance that the next word in my sentence is going to be "is." In similar fashion, supply-chain management companies such as G-Log have begun using a form of statistical analysis called stochastic optimization, first as a guidance tool for managers and later to actually automate the decision-making process."
>>> Probability, Natural Language Understanding, Business, Applications, Reasoning, Natural Language Processing

May 20, 2004: A Design Epiphany - Keep It Simple. By Jessie Scanlon. The New York Times (no fee reg. req'd.). "Dr. [John] Maeda says the solution is not better design or better technology but a better partnership between the two. Hence the Simplicity Design Workshop, which could leverage the lab's understanding of emerging technologies and the real-world experience of the designers into a series of concrete, well tested principles. ... In January Mr. [Bill] Moggridge of Ideo met with a Media Lab group led by Cynthia Breazeal, an assistant professor of media arts and sciences, to try to define simplicity. It was easy to embrace the concept, with its connotations of beauty and elegance and its promise of a better way, but what did it mean in practical terms? ... 'We started with the big picture: what does simplicity mean in the context of our work?' said Dr. Breazeal, a pioneer of social robotics whose current project is building a learning companion robot called RoCo. 'But the real value is to see how Bill approaches the problem of design.'... A third arm of research focuses on making computers smarter. One method, a new branch of artificial intelligence, aims to give computers common sense in the form of a vast database of mundane truths about the world (the sky is blue, coffee wakes you up). A second approach, affective computing, gathers information about the state of the user through a range of sensors, enabling the computer to adapt by, say, holding delivery of all but high-priority e-mail when it detects stress."
>>> Robots, Interfaces, Commonsense, Emotion, Cognitive Science, Reasoning, Representation

May 5 - 12, 2004: Chaos seems to aid learning. By Kimberly Patch. Technology Research News. " Researchers from Core Research for Evolutional Science and Technology (CREST) in Japan have built a computer simulation of the inferior olive, a portion of the brain that probably relays errors in movement to the cerebellum. It has been difficult to explain the mechanics of this relationship because inferior olive cells that connect to the cerebellum fire slowly, and this does not fit well with the common hypothesis that high-fidelity error signals are needed for efficient learning. ... In addition to allowing researchers to better understand the mechanics of the brain, the researchers' theory of chaotic resonance could speed electronic communications and improve robotics. 'In communications, our work [could] maximize the information transmitted in networks,' he said. 'In robotics, chaos could be used to explore the environment to optimize learning,' [Nicholas Schweighofer] said."
>>> Fuzzy Logic, Probablility, Logic, Reasoning, Robots, Machine Learning

May 10, 2004: Tahoka student takes byte out of competition. By P. Christine Smith. The Lubbock Avalance-Journal /available from LubbockOnline.com. "Brandon Jackson is the kind of student his science teacher would like to clone. A bright, articulate student who ranks fifth in his sophomore class, Brandon recently won a regional science fair and now is in Portland, Ore., competing in the International Science and Engineering Fair. He began his study on artificial intelligence as an eighth-grader. Brandon uses two computers, which he built, in his project 'Computers at War: How Far Can Artificial Intelligence Go?' He programmed the two computers to spar against each other in a chess-type game of his own design. Through the neuro-network, the two computers can 'learn' from each other, he said last week. ... [H]e took the project a step further and added additional programming using case-based reasoning. ... He is going up against 3,000 students from around the world at the Intel-sponsored fair in Portland, which began Sunday and runs to Friday."
>>> Competitions (@ Resources for Students), Neural Networks, Case-Based Reasoning, Chess, Machine Learning, Reasoning

April 27, 2004: Association for Computing Machinery Honors Innovators Who Changed Scientific World; David Haussler, Judea Pearl Built Bridges Beyond Computer Science. AScribe Newswire. "The Association for Computing Machinery (ACM) has recognized Dr. David Haussler and Dr. Judea Pearl for separate groundbreaking contributions that have changed the scientific world beyond computer science and engineering. Dr. Haussler was cited as possibly the most influential contributor to the field of computational biology. Dr. Pearl made seminal contributions to the field of artificial intelligence that extend to philosophy, psychology, medicine, statistics, econometrics, epidemiology and social science. As the recipients of the 2003 Allen Newell Award, they demonstrate the remarkable influence that computer science and artificial intelligence can have on other sciences, on practical tools, and on human thought. The Allen Newell Award, which is cosponsored by ACM and the American Association for Artificial Intelligence (AAAI), comes with a cash prize of $10,000."
>>> Uncertainty & Probability, Bioinformatics, Reasoning, Applications, Associations & Organizations (@ Resources for Students), AI Overview

April 27, 2004: NASA Develops Decision Support Software For Mars Mission. SpaceDaily. "'This is mission-critical software and the first application of an artificial intelligence-based system for operating a platform on the surface of another planet,' [Kanna Rajan] said, adding that MAPGEN plans out a whole day of activities for the rovers in advance. MAPGEN even decides when the rovers wake up from their nightly slumbers to begin the next 'Sol,' or martian day, of activities. MAPGEN is actually a combination of two previously built planning systems: the Activity Plan Generator (APGEN), a manually operated planner developed by JPL and EUROPA, an automated planning and scheduling system developed at Ames Research Center. An earlier version of EUROPA was flown as part of NASA's Deep Space One Remote Agent experiment in 1999."
>>> Space Exploration, Planning & Scheduling, Applications, Reasoning

April 27, 2004: Cognitive Rascal in the Amorous Swamp: A Robot Battles Spam. Essay by George Johnson. The New York Times (no fee reg. req'd.). "In Richard Powers's postmodern science fiction 'Galatea 2.2,' a young novelist, very much like the author, returns from the Netherlands to a Midwestern university, where he teaches a computer called Implementation H, or Helen, the meaning of beauty. By feeding it example after example of the world's great literature and music and engaging it in conversation, researchers hope to imbue the machine with so deep a grasp of human culture that it can pass a comprehensive master's degree examination. Instead it prefers to sing. Galatea was the name of the statue brought to life by Pygmalion, and the novel, published in 1995 by Farrar, Straus & Giroux, captures the dream of artificial intelligence: the creation of a computer so smart and engaging that you might want to keep it as a friend. Efforts nearly as ambitious continue to plod on. ... Most A.I. researchers content themselves with narrower, more practical tasks: machines that can diagnose a certain type of illness or an ailing stock portfolio, that can crawl through the World Wide Web or across the surface of Mars. Recently I've become acquainted with one of these idiot savants, a software robot called SpamProbe. Its one modest talent is learning by example to recognize junk e-mail messages and keep them from my in-box. At the heart of this and similar programs is a statistical method called Bayesian inference, a simple learning procedure that works so well in this limited domain that perhaps something like the fictional Helen is not so far-fetched after all. Within minutes, the program had discovered rules of spam identification that had taken me years to acquire. ... Bayesian statistics were invented in the 18th century by Thomas Bayes, a theologian and mathematician.... The system has been a staple of A.I. research for years. Based on what has happened in the past, a Bayesian-savvy computer can estimate the odds that it will happen again. It learns from experience through something that seems very much like the process of induction."
>>> Filtering, Probability, Commonsense, Machine Learning, Reasoning, Bayes (@ Namesakes), Applications, SciFi

April 21, 2004: Teaching Robots to Herd Cats. By Michelle Delio. Wired News. "Robots designed for emergency rescue work can survive a six-story drop onto collapsed, jagged concrete. They can be thrown 100 feet into a disaster site. They can even cope with poisonous chemicals, fires, freezing temperatures and floods. But, like most rugged individualists, they don't play well with others. ... To translate the human concept of teamwork into electronics, three teams of university researchers are working together to develop technology that would turn a pack of robots into a single machine. Led by Nikos Papanikolopoulos, researchers at the University of Minnesota, the University of Pennsylvania and Caltech are working on software that will allow small robots to coordinate their actions, carry out commands from a single human operator or take directions from a larger, smarter robot. ... Robots have to do much of this work on their own. Humans usually can't control more than three or four robots at one time. 'We've tried it -- anything over four robots and the rescuers are overwhelmed with too much information,' says Papanikolopoulos."
>>> Robots, Hazards & Disasters, Multi-Agent Systems, Vision, Planning, Reasoning, Applications

April 19, 2004: DARPA tech chief envisions the future - Sci-fi inspires Brachman to use computers in creative ways. By Frank Tiboni. Federal Computer Week. "Ron Brachman's curiosity about robots programmed to think on their own dates back to his childhood in New Jersey. It was the 1960s, 'Star Trek' first appeared on television and putting a man on the moon became a remarkable reality. ... Now Brachman works at the Defense Advanced Research Projects Agency as director of its Information Processing Technology Office, where he oversees programs that study and develop cognitive computing. He wants to solve the same problem he pondered as a teenager watching 'Star Trek' -- how to get people and computers to collaborate. Military officials think robots, with their superior memory, can aid generals in command and control centers, Brachman said. 'My sense of what it takes to put together a cognitive agent that is successful, like a really good executive assistant, is that you just don't put all these [technologies] in a pot and stir and hope that it all adds up,' he said. ... Brachman's team will take an eclectic approach to building a robot similar to Data. 'The challenge we have asked people to look at is how do we put all of these pieces together,' Brachman said. 'Maybe we don't need the world's best computer vision or speech-understanding technology. But what would happen if they both work together?'"
>>> SciFi, Reasoning, Representation, Agents, Robots, Military, Applications, Careers in AI (@ Resources for Students)

April 11, 2004: Machine rage is dead ... long live emotional computing. Consoles and robots detect and respond to users' feelings. By Robin McKie. The Observer. "Computer angst - now a universal feature of modern life - is an expensive business. But the days of the unfeeling, infuriating machine will soon be over. Thanks to break throughs in AI (artificial intelligence), psychology, electronics and other research fields, scientists are now creating computers and robots that can detect, and respond to, users' feelings. The discoveries are being channelled by Humaine, a £6 million programme that has just been launched by the EU to give Europe a lead in emotional computing. As a result, computers will soon detect our growing irritation at their behaviour and respond - by generating more sympathetic, human-like messages or slowing down the tempo of the games they are running. Robots will be able to react in lifelike ways, though we may end up releasing some unwelcome creations - like Hal, the murderous computer of the film 2001: A Space Odyssey . 'Computers that can detect and imitate human emotion may sound like science fiction, but they are already with us,' said Dr Dylan Evans, of the University of the West of England and a key Humaine project collaborator. ... A key breakthrough has been the discovery that cool, unemotional decision-making is not necessarily a desirable attribute. In fact, humans cannot make decisions unless they are emotionally involved. 'The cold, unemotional Mr Spock on Star Trek simply could not have evolved,' said artificial intelligence expert Professor Ruth Aylett of Salford University, another Humaine project leader."
>>> Emotion, Interfaces, Applications, Cognitive Science, Assistive Technologies, Robotic Pets, Video Games, Robots, Reasoning, Systems

April 7, 2004: Flood Risk Management Research Consortium (FRMRC) launched by Environment Minister Elliot Morley and Environment Agency chair Sir John Harman. Department for Environment, Food and Rural Affairs (Defra) news release. "A new floods consortium staffed by some of Britain's leading engineers and scientists and launched today by Environment Minister Elliot Morley and Environment Agency chair Sir John Harman, will invest more than £5.5m to develop more accurate flood forecasting and warning and modelling systems and improve flood management infrastructure. Its work will help reduce risk to people, their property and the environment. The new group, known as the Flood Risk Management Research Consortium (FRMRC) will pull in staff from a number of universities to work with industrial partners and operational bodies on integrated research projects, including: ... Using intelligent systems, neural networks, fuzzy set theory, artificial intelligence evolution computation (genetic algorithms), decision support tools and expert systems - to help predict the likelihood of flooding."
>>> Natural Resource Management and the Environment, Applications, Expert Systems, Neural Networks, Genetic Algorithms, Fuzzy Logic, Machine Learning, Reasoning

March 31, 2004: Conversational interface aids robot navigation. By Chappell Brown. EE Times. "Recognizing the difficulty of fully autonomous navigation, a scientist at the University of Missouri-Columbia is designing a semiautonomous approach that might have a better chance of producing useful machines in the near term. Marjorie Skubic, a computer scientist at the University of Missouri's College of Engineering, has demonstrated a prototype robot that can read sketches drawn on a PDA and then execute a proposed path through a room. Skubic is conducting the research with Missouri colleague James Keller, an expert in fuzzy-logic-based pattern recognition, and with Pascal Matsakis of the computing and information science department at Ontario's University of Guelph. ... The human director would supply the high-level cognitive understanding of the space, and the robot would execute low-level distance and motion calculations. 'It turns out that both maps and everyday conversations share a simple set of spatial elements and relationships that are used to navigate around obstacles,' said Skubic. Skubic's group is creating a robotic AI system that can understand those basic terms so that human operators would be able to direct robots through a room in an intuitive conversational mode. The goal is to create a more practical and flexible means of directing robots and autonomous vehicles. ... The underlying spatial language is based on constructing histograms representing the distance relationships between objects."
>>> Autonomous Vehicles, Fuzzy Logic, Pattern Recognition, Languages & Structures, Robots, Reasoning, Interfaces, Representation, Machine Learning, Natural Language Processing

March 27, 2004: The Isaac Newton of logic - It was 150 years ago that George Boole published his classic The Laws of Thought, in which he outlined concepts that form the underpinnings of the modern high-speed computer. By Siobhan Roberts. The Globe and Mail (page F9). "It was 150 years ago that George Boole published his literary classic The Laws of Thought, wherein he devised a mathematical language for dealing with mental machinations of logic. It was a symbolic language of thought -- an algebra of logic (algebra is the branch of mathematics that uses letters and other general symbols to represent numbers and quantities in formulas and equations). In doing so, he provided the raw material needed for the design of the modern high-speed computer. His concepts, developed over the past century by other mathematicians but still known as 'Boolean algebra,' form the underpinnings of computer hardware, driving the circuits on computer chips. And, at a much higher level in the brain stem of computers, Boolean algebra operates the software of search engines such as Google. ... The most basic and tangible example is the machinations of Boolean searches, which operate on three logical operators: and, or, not. Algebra gets factored in to this logical equation when Boole designates a multiplication sign (x) to represent 'and,' an addition sign (+) to represent 'or,' and a subtraction sign (-) to represent 'not.' ... The same 'and' gates and 'or' gates drive computer circuitry, with streams of electrons performing Boole's algebraic operations -- a computer's bits and bytes operate on the binary system, as does Boole's algebra. He employs the number 1 to represent the universal class of everything (or true) and 0 to represent the class of nothing (false). ... With his PhD in artificial intelligence, it might appear that ['Geoffrey Hinton, a computer-science professor at the University of Toronto and his great-great-grandson'] followed after Boole. But in fact, he says, 'I'm entirely on the other side.' The field of artificial intelligence, in its early years circa 1950-60, was committed to the Boolean idea that symbols effectively represent human reasoning. Since the eighties, however, artificial intelligence has come to see human reasoning as not purely logical. Rather, it is more about what is intuitively plausible. 'Boole thought the human brain worked like a pocket calculator or a standard computer,' Prof. Hinton says. 'I think we're more like rats.'"
>>> Systems & Languages, History, Logic, Boole (@ Namesakes), Reasoning, Web-Searching Agents, Cognitive Science, Information Retrieval

March 22, 2004: Sharp unit to license IP from U.S. labs. By R. Colin Johnson. EE Times. "Artificial-intelligence technology that could change the way busy sports fans get their fix will be among the licensable intellectual property unveiled here Tuesday (March 23) by the newly formed Sharp Technology Ventures. ... One technology that could find a wide audience is Sharp's HiMpact Sports, which applies a set of algorithms that understand the semantics of baseball, football and soccer (for starters) and can boil down a three-hour game to 45 minutes without skipping a single play. ... How can Sharp Labs teach a computer to recognize a base hit regardless of whether it's a grounder, a line drive or a bunt? Traditional AI would extract features from the video stream, then use handwritten rules to infer the meaning (base hit) from the features. After extensive testing, however, Sharp Labs concluded that its requirement that HiMpact provide 100 percent accuracy could only be met by probabilistic methods that directly learn from experience. ... The best probabilistic method Sharp Labs has tried thus far is the hidden Markov model (HMM), which has previously been successful in learning how to recognize spoken voices. Just as HMM is 'taught' words by training it with samples of different people speaking the same word, Sharp Labs trained its HMM on video clips it categorized into a training set."
>>> Information Retrieval, Image Understanding, Probability, Reasoning, Machine Learning, Sports, Markov (@ Namesakes), Vision, Speech, Applications

March 17, 2004: RFID chips watch Grandma brush teeth. By Celeste Biever. New Scientist News. "Tiny computer chips that emit unique radio-frequency IDs could be slapped on to toothbrushes, chairs and even toilet seats to monitor elderly people in their own homes. Data harvested from the RFID chips would reassure family and care-givers that an elderly person was taking care of themselves, for example taking their medication. Unusual data patterns would provide an early warning that something was wrong. A group of Intel researchers demonstrated the technology to US government officials in Washington DC on Tuesday. ... Algorithms on the PC use 'probabilistic' reasoning to infer what the person is doing. For some tasks, merely picking up an object such as a toothbrush is enough. But to determine that someone is making a cup of tea, a series of objects and their order must also be known. Concerned relatives can then check on their loved one over the internet. The computer could even be programmed to pick up on unusual patterns automatically and alert relatives through an email or SMS message. ... Other companies and universities also showcased wireless healthcare technologies including a bed that monitors a person's weight and movements. Larson's team at MIT demonstrated embedded systems that rely on a network of embedded cameras and temperature sensors to make inferences about behaviour."
>>> Assistive Technologies, Uncertainty/Probability, Machine Learning, Reasoning, Applications

February 19, 2004: Know your imitations - From cameras and fridges to business solutions, artificial intelligence is at work. By Mary Branscombe. The Guardian. "Computers like things precise: on or off, one or zero, yes or no. The real world is rarely precise or exact; information is partial and uncertain and people make judgment calls. Artificial intelligence is about making computers act more like humans and you might be surprised at how many places it's showing up - from cameras and fridges to spam filters and Microsoft's forthcoming BizTalk Server 2004. If AI makes you think of robots and artificial brains, think again. Researchers are still arguing about whether a computer could actually think or just respond as if it can, but the results of their research are too useful to stay in the lab. Software can act in ways we think of as intelligent, can deliver results we'd only expect from a human, and can let us work in ways that feel more natural."
>>> AI Overview, Applications, Video Games, Household Appliances, Fuzzy Logic, Bayes (@ Namesakes), Probability, Filtering, Interfaces, Expert Systems, Banking, Business, Reasoning

February 12, 2004: Vulcan project aims to build 'Digital Aristotle'. By Luke Timmerman. The Seattle Times. "[Paul] Allen's private investment company, Vulcan, is announcing today that it is willing to bankroll three competing research teams from around the world for what it calls 'Project Halo,' a quest over the next 30 months to create a computerized tutor that's smart enough to pass college-level Advanced Placement (AP) tests in chemistry, biology and physics. Vulcan is trying to avoid being linked with forays into artificial intelligence -- colossally hyped flops since the 1980s that crumbled under sci-fi dreams of mimicking human motivation or emotion. This effort, they say, is more about 'knowledge representation and reasoning,' synthesizing existing information to produce not just a yes/no answer but a lucid explanation. ... 'This is not going to be a sentient computer or have self-awareness or emotion or anything like that,' [Noah] Friedland said. 'We're going to have a hard-enough time with common-sense issues. But this is going to reason about science and be used as a tool for learning.'"
>>> Reasoning, Representation, Commonsense, Emotion, AI Overview, Turing Test

February 8, 2004: Reasoning on the Web with rules and semantics. By Ibn Campusino. The Sunday Times (Malta). "In the framework of its sixth Framework Programme, the European Commission has decided to launch a research 'Network of Excellence' on 'Reasoning on the Web' entitled REWERSE (for REasoning on the WEb with Rules and SEmantics). ... The objective of REWERSE is to strengthen Europe in the area of reasoning languages for Web systems and applications, especially Semantic Web systems and applications aiming at enriching the current Web with so-called intelligent capabilities for data and service retrieval, composition, and processing."
>>> Reasoning, Representation, Languages & Structures, Ontologies, Web-Searching Agents, Information Retrieval, Applications

January 19, 2004: Follow The Water - Robotic Mission To Martian Soil Is A Search For Life. By Nivedita Mookerji. The Financial Express. "There's also a strong Indian connection, when we talk about Mission Mars. Soon after its landing, Spirit began its scientific tasks. And many of these tasks are being controlled, operated and monitored by the software developed by a NASA team led by Kanna Rajan, a 1990 computer science and engineering master's graduate from the University of Texas at Arlington (UTA). Mr Rajan is now a principal investigator and senior scientist at NASA Ames Research Center in Moffett Field, California. According to reports published by NASA on its home page, Mr Rajan and his team's software, called 'MAPGEN (Mixed-Initiative Activity Plan GENerator), for building activity plans with complex constraints and dependencies, is the first published artificial intelligence-based system to command a rover on another planet.' Mr Rajan, while speaking to eFE (see interview), said: 'MAPGEN produces an initial plan automatically, using state-of-the-art Artificial Intelligence (AI) techniques that we've been working on at NASA Ames Research Center over the last 10 years, to produce a conflict free plan. It is conflict free, in terms of activities that do not clash.'"