To integrate robotics into society, it is first necessary to measure and analyze current societal responses to areas within robotics. This article is the second in a continuing series of reports on the societal effects of various aspects of robotics. In my previous article, I discussed the problems of sensor abuse and outlined a program of treatment. However, despite the wide dissemination of that article, there are still numerous empty beds at the Susan Calvin Clinic for the Prevention of Sensor Abuse. Sensor abuse continues unabated despite strong evidence that there is a better way.

However, I believe that the distinction of "neats" and "scruffies" raised at Cog Sci in '81 didn't define scruffies as people who built expert systems [they didn't really exist as a "real" part of MAD. Instead, I believe AI These are the researchers who read Hawkings and say "gee, if his model of the lo-23 second big bang is right, then the distribution of intergalactic gases should be relatively even. Let's go see if that's true. However, to run our experiments we'll need a more sensitive space-based sensing device, so let's work with the engineers to design one." I think one could make the case (although not from the data collected in Cohen's survey) that the two methodologies are not informed and influenced by each other to the extent they should or could be.

The Journal of Artificial Intelligence Research (JAIR) was one of the first scientific journals distributed over the web. It has now completed over five years of successful publication. Electronic publishing is reshaping the way academic work is disseminated, and JAIR is leading the way toward a future where scientific articles are freely and easily accessible to all. This report describes how the journal has evolved, its "grassroots" philosophy, and prospects for the future. By August, JAIR had reviewed, accepted, and published 2 articles and rejected 18 others.

The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (Greenbelt, Md.) has developed the The system is designed to capture and maintain key scientific knowledge while it reduces common errors made by outside scientists. Johnson Controls (Milwaukee, Wis.), a manufacturer of control products used to monitor buildings, has deployed an intelligent agent-based knowledge-retrieval solution at its help desk to provide fast access to support information. Chester, N.Y.) to improve its ability to match reported wage information. The solution will help the agency match contribution information supplied by employers to an employee's Social Security account. RoyScot Trust, the asset finance arm of the Royal Bank of Scotland (Edinburgh, Scotland), has implemented an expert system-based solution to automate the credit-underwriting process.

We made it to the end of a tumultuous year of political turmoil, technological change and legislative upheaval. The fact we made it to New Year's Eve without starting a nuclear war with North Korea is all the more reason to celebrate. Many of this year's biggest events, like GDPR, developments in AI and the disjointed launch of the iPhone X, took place at the very epicentre of marketing, with repercussions that are still making headlines to this day. So with the start of a new year, it's time to look back as well as forwards and ask: what will the last twelve months mean for marketing in 2018? Nobody knows how last year's referendum will affect the UK, and as a result, uncertainty continues to hover over business, with some firms making the move to the continent.

There has been a flurry of interest recently in the possibility of standardizing existing work on knowledge representation; this interest is supported by the Defense Advanced Research Projects Agency (DARPA) and other funding agencies. An examination of recent work on knowledge representation makes it clear that there are deep differences among the approaches taken. Those supporting knowledge representation standards are attempting to address this difficulty by creating a single language in which all knowledge representation schemes can be expressed (Genesereth 1990), but this task seems impossible given the current state of the field. However, it is surely not possible to construct a language that will also incorporate all future knowledge representation work, other than in the trivial sense guaranteed by the universality of some specific method, such as first-order logic or a general-purpose programming language. Furthermore, attempts in this direction will inevitably constrain future knowledge representation efforts; even gentle constraints might have a stifling impact on future knowledge representation work.

Randy Davis announced the appointment of six new program managers at ARPA. He encouraged individuals to contact these managers to see where they can help. At IJCAI-95, Randall Davis assumed the office of president of the American Association for Artificial Intelligence (AAAI). Davis is a professor of electrical engineering and computer science and associate director of the AI Lab at the Massachusetts Institute of Technology (MIT). Davis succeeds Barbara Grosz, Gordon McKay professor of computer science in the Division of Applied Sciences at Harvard University.

IAAI has been held annually since 1989 and has been collocated with the national (or international) AI conference since 1991. The proceedings were published in book form through 1992. Since 1993, a conference proceedings volume has been published, and selected papers have been republished as articles in AI Magazine. This introduction briefly discusses the 1995 IAAI award winners and presents goals and plans for next year's conference. IAAI features real, deployed AI applications, selected for their innovation.

Reports from some of these first projects make up the majority of the book, with the balance of the book providing an overview of neuroinformatics. The book's foreword provides interesting history and perspective on the incubation of neuroinformatics. The preface and first two chapters of the book explain neuroinformatics and the motivation for it. As with so many other fields, there has been an information explosion in neuroscience research. Data are produced by tens of thousands of investigators in hundreds of journals.

In a large-scale space, structure is at a significantly larger scale than the observations available at an instant To learn the structure of a large-scale space from observations, the observer must build a cognitive map of the environment by integrating observations over an extended period of time, inferring spatial structure from perceptions and the effects of actions The cognitive map representation of largescale space must account for a mapping, or learning structure from observations, and navigation, or creating and executing a plan to travel from one place to another Approaches to date tend to be fragile either because they don't build maps; or because they assume nonlocal observations, such as those available in preexisting maps or global coordinate systems, including active Thus, to learn the large-scale structure of the space, the traveler must necessarily build a cognitive map of the environment by integrating observations over extended periods of time, inferring spatial structure from perceptions and the effects of actions. Large-scale space and the corresponding cognitive map representation cannot be defined independent of sensory perceptions or motor actions used to observe and move about in this environment For example, a work bench observed by a laser-bearing robot is not a large-scale space, but the moon is a large-scale space relative to a land-roving robot. A microchip is not large scale relative to an optical inspection system, but a grasshopper ganglion is a large-scale space when observed by an electron microscope. Inverse trigonometric operations and scalar multiplication require ratio data, in which a numeric value is calibrated with respect to a true zero. Trigonometric operations can require only interval data on angles, where differences are well defined, but absolute angles are not required.