Who wouldn’t pay a penny for a sports car? That’s the mentality some popular online auctions take advantage of — the opportunity to get an expensive item for very little money.
In a study of hundreds of lowest unique bid auctions, Northwestern University researchers asked a different question: Who wins these auctions, the strategic gambler or the lucky one? The answer is the lucky. But, ironically, it’s a lucky person using a winning strategy.
The researchers found that all players intuitively use the right strategy, and that turns the auction into a game of pure chance. The findings, published by the journal PLoS One, provide insight into playing the stock market, real estate market and other gambles.
Princeton University researchers have used a novel virtual reality and brain imaging system to detect a form of neural activity underlying how the brain forms short-term memories that are used in making decisions.
By following the brain activity of mice as they navigated a virtual reality maze, the researchers found that populations of neurons fire in distinctive sequences when the brain is holding a memory. Previous research centered on the idea that populations of neurons fire together with similar patterns to each other during the memory period.
The study was performed in the laboratory of David Tank, who is Princeton’s Henry L. Hillman Professor in Molecular Biology and co-director of the Princeton Neuroscience Institute. Both Tank and Christopher Harvey, who was first author on the paper and a postdoctoral researcher at the time of the experiments, said they were surprised to discover the sequential firing of neurons. The study was published online on March 14 in the journal Nature. Continue reading »
Artificial Intelligence offers many possibilities for developing data processing systems which are more precise and robust. That is one of the main conclusions drawn from an international encounter of experts in this scientific area, recently held at Universidad Carlos III de Madrid (UC3M).
Artificial Intelligence offers many possibilities for developing data processing systems which are more precise and robust. (Credit: UMC3)
Within this framework, five leading scientists presented the latest advances in their research work on different aspects of AI. The speakers tackled issues ranging from the more theoretical such as algorithms capable of solving combinatorial problems to robots that can reason about emotions, systems that use vision to monitor activities, and automated players that learn how to win in a given situation. “Inviting speakers from groups of references allows us to offer a panoramic view of the main problems and the techniques open in the area, including advances in video and multi-sensor systems, task planning, automated learning, games, and artificial consciousness or reasoning,” the experts noted.
The participants from the AVIRES (The Artificial Vision and Real Time Systems) research group at the University of Udine gave a seminar on the introduction of data fusion techniques and distributed artificial vision. In particular, they dealt with automated surveillance systems with visual sensor networks, from basic techniques for image processing and object recognition to Bayesian reasoning for understanding activities and automated learning and data fusion to make high performance system. Dr.Simon Lucas, professor at the Essex University and editor in chief of IEEE Transactions on Computational Intelligence and AI in Games and a researcher focusing on the application of AI techniques on games, presented the latest trends in generation algorithms for game strategies. During his presentation, he pointed out the strength of UC3M in this area, citing its victory in two of the competitions held at the international level during the most recent edition of the Conference on Computational Intelligence and Games.
In addition, Enrico Giunchiglia, professor at the University of Genoa and former president of the Council of the International Conference on Automated Planning and Scheduling (ICAPS), described the most recent work in the area of logic satisfaction, which is rapidly growing due to its applications in circuit design and in task planning
Artificial Intelligence (IA) is as old as computer science and has generated ideas, techniques and applications that permit it to solve difficult problems. The field is very active and offers solutions to very diverse sectors. The number of industrial applications that have an AI technique is very high, and from the scientific point of view, there are many specialized journals and congresses. Furthermore, new lines of research are constantly being open and there is a still great room for improvement in knowledge transfer between researchers and industry. These are some of the main ideas gathered at the 4th International Seminar on New Issues on Artificial Intelligence), organized by the SCALAB group in the UC3M Computer Engineering Department at the Leganés campus of this Madrid university.
The future of Artificial Intelligence
This seminar also included a talk on the promising future of AI. “The tremendous surge in the number of devices capable of capturing and processing information, together with the growth of the computing capacity and the advances in algorithms enormously boost the possibilities for practical application,” the researchers from the SCALAB group pointed out. Among them we can cite the construction of computer programs that make life easier, which take decisions in complex environments or which allow problems to be solved in environments which are difficult to access for people,” he noted. From the point of view of these research trends, more and more emphasis is being placed on developing systems capable of learning and demonstrating intelligent behavior without being tied to replicating a human model.
AI will allow advances in the development of systems capable of automatically understanding a situation and its context with the use of sensor data and information systems as well as establishing plans of action, from support applications to decision making within dynamic situations. According to the researchers, this is due to the rapid advances and the availability of sensor technology which provides a continuous flow of data about the environment, information that must be dealt with appropriately in a node of data fusion and information. Likewise, the development of sophisticated techniques for task planning allow plans of action to be composed, executed, checked for correct execution, and rectified in case of some failure, and finally to learn from mistakes made.
This technology has allowed a wide range of applications such as integrated systems for surveillance, monitoring and detecting anomalies, activity recognition, teleassistence systems, transport logistic planning, etc. According to Antonio Chella, Full Professor at the University of Palermo and expert in Artificial Consciousness, the future of AI will imply discovering a new meaning of the word “intelligence.” Until now, it has been equated with automated reasoning in software systems, but in the future AI will tackle more daring concepts such as the incarnation of intelligence in robots, as well as emotions, and above all consciousness.
One hundred and fifty-one years after the publication of On the Origin of Species, digital creatures have evolved to communicate like fireflies in a computer program that blurs the boundaries of life.
Recorded in line-by-line detail, their development in a software platform called Avida may provide insight into biological behavior and inspiration for the design of distributed computer networks.
“Evolutionary programs have been around for a while, but we haven’t seen them applied to distributed computing,” said computer scientist Philip McKinley of Michigan State University. Synchronized communication can be “seen in the natural world. But in Avida, we can go back to how and why it evolved. We can see the key points that allowed this relatively complex behavior to emerge.”
The new synchronization findings, made by McKinley and fellow MSU computer scientist David Knoester, were published November 18 in Artificial Life.
Inside the program, developed in the early 1990s at the California Institute of Technology and refined at MSU’s Digital Evolution Laboratory, digital organisms called Avidians take the form of self-replicating code. Their genomes are written in assembly language and stored in separate regions of memory, executed again and again at electronic speeds. Programmers set the parameters of mutation and natural selection, and evolutionary principles manifest themselves in silico.
“We like to say ‘it’s not a simulation of evolution, it’s evolution.’ The difference is that these are computer programs,” McKinley said.
In a previous and well-known study, researchers supported a key tenet of evolutionary theory by demonstrating how easily complexity could emerge in Avidians through incremental changes in simple, existing functions.
McKinley and Knoester specialize in organismal interactions: How complexity emerges not only in individuals, but also in groups.
Their earlier work examined the evolution of collective perception, cooperation and decision making. In the new study, however, they emphasized communication and selected for groups of Avidians that best synchronized their flashing with others.
Fireflies, which coordinate their blinking across distances spanning miles, are the best-known synchronized communicators of the biological world. How they do it isn’t fully understood, but Knoester said “it was literally a three- or four-line change” in Avida.
Crucial to Avidian synchronization was the handling of the computational version of “junk DNA,” or genetic code that seems to have no apparent purpose. In biology, junk DNA is now appreciated as having crucial regulatory functions. In the Avidians, individuals evolved to change their flash timing by adjusting the speed at which “junk” instructions were executed.
McKinley and Knoester don’t think that fireflies necessary synchronize the same way, as Avida provided a computational and likely different route to the same outcome. More importantly, it gave the researchers algorithms they would not have otherwise imagined.
The algorithms could inspire functional code beyond Avida’s confines.
“Avidians build network topologies. What sort of topologies do they come up with that are robust to damage, if the routing nodes fail?” Knoester said. “We’re also collaborating with a professor in the electrical engineering department who works on robotic fish. We’re not really interested in schooling; we want robots to track oil slicks, to monitor water quality. To do those things, you need to stay connected.”
As for the upper limit on Avidian complexity, “I’m not sure we know yet,” Knoester said.
Video: Organisms in Avida, a software platform for artificial life, running their genomic instructions. Eventually they evolve to flash in synchrony, like fireflies./Philip McKinley and David Knoester.