In 1950, when Turing proposed to replace the question "Can machines think?" with the question "Are there imaginable digital computers which would do well in the imitation game?" computer science was not yet a field of study, Shannon’s theory of information had just begun to change the way people thought about communication, and psychology was only starting to look beyond behaviorism. It is stunning that so many predictions in Turing’s 1950 Mind paper were right. In the decades since that paper appeared, with its inspiring challenges, research in computer science, neuroscience, and the behavioral sciences has radically changed thinking about mental processes and communication, and the ways in which people use computers has evolved even more dramatically. Turing, were he writing now, might still replace "Can machines think?" with an operational challenge, but it is likely he would propose a very different test. This paper considers what that might be in light of Turing’s paper and advances in the decades since it was written.

At one of those conferences, I met John. Stanford moved toward a computer science department under the leadership of George Forsythe, John suggested to George, and then supported, the idea of hiring me into the founding faculty of the department. Since we were both Advanced Research Project Agency (ARPA) contract awardees, we quickly formed a close bond concerning ARPA-sponsored AI research and graduate student teaching. And the joint intelligence of both of us was quickly deployed in a very rapid and, in retrospect, brilliant decision to hire Les Earnest to be the executive officer of the new Stanford AI Lab that ARPA supported. John McCarthy's first breakthrough paper was his 1958 Teddington Symposium paper on programs with commonsense reasoning abilities.

"Information processing" is a not-so-long-ago launched buzzword that is extensively used in many research fields and communities. Despite of its widespread popularity, the real meaning of it is far less acknowledged and understood. Wikipedia [1] and Plato (Stanford Encyclopedia of Philosophy) [2] provide special entries for it, but even in the lightest manner, these entries do not confront the threatening ambiguity and incomprehensibility of this expression. Positing that "Information processing is the change (processing) of information "[1] in any way does not clarify its elusive essence. The reason for that is simple - the key component of the expression ("information") has never been defined and never determined, neither in the times of ancient philosophers nor in these glorious days, when "information era" has become our blossoming reality. It is worth to be mentioned - even today "information" does not have an accepted and a generally agreed definition. Far worse than that - it has always been (and continues to be) a "bone of contention" between many prominent thinkers, scholars and scientists. I do not intend to take part in this controversy. In the paper's Reference section I provide a list of some relevant publications addressing this issue, with only one and a definite purpose in mind - to give the vigilant readers a fair opportunity to verify by themselves how useful and applicable are the concepts of information that these leading thinkers and scholars are developing and advance (L.

Many cognitive systems deploy multiple, closed, individually consistent models which can represent interpretations of the present state of the world, moments in the past, possible futures or alternate versions of reality. While they appear under different names, these structures can be grouped under the general term of worlds. The Xapagy architecture is a story-oriented cognitive system which relies exclusively on the autobiographical memory implemented as a raw collection of events organized into world-type structures called {\em scenes}. The system performs reasoning by shadowing current events with events from the autobiography. The shadows are then extrapolated into headless shadows corresponding to predictions, hidden events or inferred relations.

He has been chairman/president the MIT Artificial Intelligence Lab. Board of Trustees, as well as treasurer 100 Americans most likely to shape Manuela Veloso, incoming AAAI President, of SSAISB and ECCAI. He is presently the next century; TIME Digital selected and Eric Horvitz, AAAI Past editor-in-chief of the AAAI Press, Spatial her as a member of the Cyber-Elite; President and Awards Committee Cognition and Computation, and the World Economic Forum honored Chair, presented the AAAI Awards in the Artificial Intelligence Journal. He was her with the title Global Leader for Tomorrow; August at AAAI-12 in Toronto. She holds bachelor's and or 1-650-328-3123.)

This article is the first report in the best of AI in Japan series. This series will focus on the prominent accomplishments made in the AI field, not only the research and development but also the AI-related events in society. As the first in the forthcoming series, this opening article features a historical background and the contemporary AI-research activities in Japan. It then highlights some recent prominent results from the industry. Finally, a future perspective is given.

The AAAI-12 technical Christos Papadimtriou (University of abstracts, and poker competition program will kick off with the opening California, Berkeley) will deliver the posters.

NewsFinder automates the steps involved in finding, selecting, categorizing, and publishing news stories that meet relevance criteria for the Artificial Intelligence community. The software combines a broad search of online news sources with topic-specific trained models and heuristics. Since August 2010, the program has been used to operate the AI in the News service that is part of the AAAI AITopics website.

Deregulation of energy markets, penetration of renewables, advanced metering capabilities, and the urge for situational awareness, all call for system-wide power system state estimation (PSSE). Implementing a centralized estimator though is practically infeasible due to the complexity scale of an interconnection, the communication bottleneck in real-time monitoring, regional disclosure policies, and reliability issues. In this context, distributed PSSE methods are treated here under a unified and systematic framework. A novel algorithm is developed based on the alternating direction method of multipliers. It leverages existing PSSE solvers, respects privacy policies, exhibits low communication load, and its convergence to the centralized estimates is guaranteed even in the absence of local observability. Beyond the conventional least-squares based PSSE, the decentralized framework accommodates a robust state estimator. By exploiting interesting links to the compressive sampling advances, the latter jointly estimates the state and identifies corrupted measurements. The novel algorithms are numerically evaluated using the IEEE 14-, 118-bus, and a 4,200-bus benchmarks. Simulations demonstrate that the attainable accuracy can be reached within a few inter-area exchanges, while largest residual tests are outperformed.

Posters, the AAAI/SIGART Doctoral of AAAI; submit papers to the conference Consortium, and more!