Appl. Intell.最新文献

{"title":"Conference review: IFIP TC12","authors":"S. Shapiro","doi":"10.1145/383824.383826","DOIUrl":"https://doi.org/10.1145/383824.383826","url":null,"abstract":"I attended the annual meeting of IFIP TC12 on August 6, 2001, during IJCAI in Seattle, as the ACM representative. IFIP is the International Federation for Information Processing. It was established in 1960 under the auspices of UNESCO, and is a society of societies. That is, the members of IFIP are not people, but societies and associations. Mostly, there is one member from each country, serving as the representative of computing activities and people in that country. The United States is an exception. Instead of a single society representing the United States, ACM and IEEE are members of IFIP, even though both of these are international, not national organizations. IFIP technical work is managed by a set of 12 Technical Committees, devoted to various aspects of the field of computing. I am the ACM representative to TC12, Artificial Intelligence. The stated aim of TC12 is, “Research in AI and promotion of interdisciplinary exchange between AI and other fields of information processing,” and its scope is to, “Further develop the foundation for AI on the basis of computer science principles. Contribute techniques from AI to the enrichment of computer science and information processing. Develop AI techniques as part of information processing technologies to enable and advance practical applications.” [www.ifip.or.at/bulletin/bulltcs/tc12_aim.htm] IFIP TCs, in turn, have working groups as part of them. TC12 has two active working groups: WC 12.5, KnowledgeOriented Development of Applications and WG 12.6 Intelligent Information Management. TC12 meets annually during an international AI meeting. As I said above, this year’s meeting was held during IJCAI in Seattle. Nine of the 24 members were present, including the chair, Bernd Neumann, representing Germany’s Gesellschaft für Informatik, and the Secretary, Dan O’Leary, representing IEEE. At the meeting, there was some discussion of what IFIP does. The main message I got from this is that IFIP will cooperate with international conferences, and is especially good at marketing and publications. It usually wants a share of the revenues, but this is negotiable. In fact, it may be possible to get financial support from IFIP. If you are planning a conference, it would be a good idea to discuss it with them. You should start discussions with Prof. Neumann or me, as TC support is important. We specifically discussed support for student attendance, and, especially, given the UNESCO connection, support for attendance from underdeveloped countries. A major part of the meeting was devoted to the upcoming international conference on Intelligent Information Processing (IIP-2002), part of the IFIP World Computer Congress, to be held in Montreal, August 25-30, 2002. The IIP conferences are organized by TC12. IIP-2002 will have two tracks: Knowledge-Based System Architecture, and Intelligent Information Management. It will also have five linkage sessions, which are being organized in cooperation with other TCs. The link","PeriodicalId":8272,"journal":{"name":"Appl. Intell.","volume":"51 1","pages":"6"},"PeriodicalIF":0.0,"publicationDate":"2001-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90243435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Curriculum descant: machine learning for the masses","authors":"C. Congdon, Deepak Kumar","doi":"10.1145/378116.378118","DOIUrl":"https://doi.org/10.1145/378116.378118","url":null,"abstract":"read additional material on other forms of machine learning to broaden their view of what the field includes, while not becoming overwhelmed with details of implementation. Useful data sets can often be obtained from faculty members in other departments on campus. Faculty members in other departments are likely to use other approaches (such as logistic regression) when analyzing their data, and some will welcome having a student try an entirely different approach to gain insight into the problem. The students, in turn, are able to see their computer science talents as useful relative to questions in another discipline. Another reason the course is attractive is that a teacher can give students the opportunity to use and modify large software systems. Several machine learning systems are available for downloading, for example, Students can be exposed to a culture where data sets and code are shared and can be expected to become oriented to a large system and make changes or extensions to a specific part of such a system. An undergraduate course in machine learning can be offered to a wide range of students, with minimal prerequisites, for example, to students who have completed a data structures course. Not even an artificial intelligence course need be a prerequisite; however, key topics such as search, heuristics, and representation must be introduced. Whereas a graduate level machine learning course is often structured to read scores of journal papers that describe different systems (perhaps working with three or four systems), an undergraduate-level course can eschew the \" breadth \" of machine learning and adopt a specific focus, Machine Learning for the Masses curriculum descant F ormerly considered an esoteric subfield of computer science, machine learning is now seeing broad use in computer science applications. It is used, for example, in search engines, computer games, adaptive user interfaces, personalized assistants, Web bots, and scientific applications. However, few colleges and universities require a course in machine learning as part of an undergraduate major in computer science. It is time for us as computer science educators to recast an introduction to machine learning concepts as a staple of a computer science education. Many possible flavors of machine learning might be emphasized, and in a one-course introduction to the field, a student must chart a course consistent with the educational environment and the instructor's background. For example, you might focus a course on a particular approach to machine …","PeriodicalId":8272,"journal":{"name":"Appl. Intell.","volume":"137 1","pages":"15-16"},"PeriodicalIF":0.0,"publicationDate":"2001-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86616533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Backtracking: the nine lives of the AI","authors":"Syed S. Ali","doi":"10.1145/378116.378128","DOIUrl":"https://doi.org/10.1145/378116.378128","url":null,"abstract":"","PeriodicalId":8272,"journal":{"name":"Appl. Intell.","volume":"14 1","pages":"56-"},"PeriodicalIF":0.0,"publicationDate":"2001-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74506325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Creating natural language ouput for real-time applications","authors":"S. McRoy, S. Channarukul, Syed S. Ali","doi":"10.1145/378116.378122","DOIUrl":"https://doi.org/10.1145/378116.378122","url":null,"abstract":"","PeriodicalId":8272,"journal":{"name":"Appl. Intell.","volume":"91 1","pages":"21-34"},"PeriodicalIF":0.0,"publicationDate":"2001-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85148018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Links: artificial intelligence and interactive entertainment","authors":"R. Amant, R. Young","doi":"10.1145/378116.378120","DOIUrl":"https://doi.org/10.1145/378116.378120","url":null,"abstract":"A s John Laird pointed out in his IAAI/AAAI invited talk last year, artificial intelligence (AI) research and computer gaming have quite a bit to offer each other. Although many commercially successful computer games have been rather vis-ceral and violent, AI techniques offer the promise of creating engaging and dynamic interactive entertainment with strong narrative components. For AI researchers working in the context of computer games, research challenges are as complex and compelling as many real-world problem areas; gaming environments offer unique interfaces and modes of use and an extensive existing base of potential users. In this article, we introduce some aspects of the application of artificial intelligence research to interactive entertainment. Although intelligent techniques certainly apply to a wide range of computer games, here we will focus on games that simulate or create highly interactive virtual envi-ronments—games in which one or more users control various aspects of the game's world, either in discrete steps (for example, turn-taking) or in continuous real-time modes. These kinds of computer games are excellent environments for artificial intelligence researchers to explore for several reasons. First, as testbeds for AI systems computer games provide a unique combination of simulation and reality. That is, the environment in which a computer game user interacts is virtual, but that environment is not a simulation of the problem domain; it is the problem domain. As a result, AI researchers can choose to side-step issues such as noisy sensor data, imperfect effectors, or other complications often found in real-world problems and still address realistic problems in the game environment. Second, gaming environments pose a range of problems, at both the strategic and interface levels. Strategic-level challenges in computer games can involve mapping or choosing between complex strategies, refining components of a strategy by formulating context-specific move sequences, and detecting and responding to human users' actions. At the interface level, intelligent components inside a game must control how the game world is presented to the users. Perhaps a unique property of 3-D game environments is that, in many aspects, they are their own interface. That is, every aspect of a game's virtual e n v i r o n m e n t — i t s objects, characters, lighting , sound, and camera— can be exploited by the system to create an overall effective interaction. Recent research has addressed many of the issues at the interface level (for example, the …","PeriodicalId":8272,"journal":{"name":"Appl. Intell.","volume":"39 1","pages":"17-19"},"PeriodicalIF":0.0,"publicationDate":"2001-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78725665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Conference review: Semantic Web Workshop:: models, architectures and management","authors":"P. Constantopoulos, V. Christophides, D. Plexousakis","doi":"10.1145/378116.378124","DOIUrl":"https://doi.org/10.1145/378116.378124","url":null,"abstract":"i n t e l l i g e n c e • S u m m e r 2 0 0 1 39 Introduction In 1998 the World-Wide Web Consortium (W3C) inaugurated a research initiative centered on the idea of providing semantics for and facilitating the extraction of knowledge from the World-Wide Web. The Semantic Web is a vision of the creator of the WWW, Tim Berners-Lee, who describes it as “a Web of data, documents, or portions of documents, that can be processed directly or indirectly by machines” not just for display purposes, but for automation, integration and reuse across various applications. The primary goal of the Semantic Web is to define infrastructure, standards, and policies facilitating an explicit description of the meaning of Web resources that can be processed both by automated tools and people. This effort towards the next evolution step of the Web has given rise to a large number of research problems that relate to models, architectures, applications, and services for the Semantic Web. The following is a list of research issues that were put forth as themes for soliciting workshop submissions. ✦ Formal Foundations of Web Metadata Standards ✦ Semantic Interoperability Frameworks ✦ Information and Services Brokering Architectures ✦ Metadata Creation, Extraction, and Storage ✦ Query Languages for the Semantic Web ✦ Distributed Inference Services ✦ Digital Signatures and Web of Trust ✦ Advanced Resource Discovery Interfaces ✦ Automated Classification of Web Resources ✦ Superimposed Web Resource Annotation & RecommendationTools ✦ Personalization and Intellectual Property Rights ✦ Semantic Web Applications: Knowledge Portals, Electronic Commerce The objective of the workshop was the creation of a forum for presenting research results in developing infrastructure for the Semantic Web and for enabling and fostering interaction among international researchers. The collocation of the workshop with the European Conference on Digital Libraries broadened the intended scope of the workshop and attracted participation and interaction from industry in addition to the academic and research communities. The workshop’s audience comprised researchers and practitioners in the areas of databases, intelligent information integration, knowledge representation, knowledge management, information retrieval, metadata, Web standards, digital libraries, and others. The workshop was organized as a post-conference one-day workshop at ECDL 2000 in Lisbon, Portugal. Panos Constantopoulos chaired the workshop committee with Vassilis Christophides and Dimitris Plexousakis as Program Committee Co-Chairs. A total of 29 papers were submitted to the workshop. Each paper was peer-reviewed by at least two referees. Despite the overall high quality of the submissions, only nine papers were accepted by the program committee for presentation at the single-day event. Overall, the workshop drew considerable attention at ECDL 2000: 63 registered participants from 22 countries. The workshop was sponsored by ERCIM (the","PeriodicalId":8272,"journal":{"name":"Appl. Intell.","volume":"22 1","pages":"39-44"},"PeriodicalIF":0.0,"publicationDate":"2001-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76754868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Backtracking: the eternal flame","authors":"Chris Welty","doi":"10.1145/376451.376470","DOIUrl":"https://doi.org/10.1145/376451.376470","url":null,"abstract":"","PeriodicalId":8272,"journal":{"name":"Appl. Intell.","volume":"48 1","pages":"39-40"},"PeriodicalIF":0.0,"publicationDate":"2001-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88414400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Links: AI planning resources on the Web","authors":"R. Amant, R. Young","doi":"10.1145/376451.376464","DOIUrl":"https://doi.org/10.1145/376451.376464","url":null,"abstract":"W ith the introduction of new, efficient techniques for planning, interest in the field has risen sharply in recent years. Planning systems have come a long way since the days of Blocks World. Today, planning and scheduling techniques are being used to solve problems in military campaign planning, robot navigation, industrial equipment scheduling, human-computer interaction, and many other real-world domains. Planning, which is the process of finding a sequence of actions that meets an agents goal, is a thriving area of artificial intelligence (AI) research and is growing almost faster than one can keep track. Fortunately, an abundance of information about planning is available, in both paper and electronic forms; answers to most of the questions a newcomer to the field might ask can easily be found. Early approaches to planning , as exemplified by STRIPS (Stanford Research Institute Problem Solver), viewed the planning problem as that of generating a sequence of operators that will transform the current state of the environment into a goal state. This approach is sometimes referred to in the planning literature as \" state space search. \" Eventually a different perspective gained dominance , in which states represented not properties of the environment but the plans being considered. That is, rather than searching through a space of world states, planning systems searched through a space of partially elaborated plans. Penberthy and Weld's UCPOP, a partial-order planner, is one of the best known examples of this approach. More recently, with the development of the Graphplan algorithm by Blum and Furst, another conceptual shift has taken place. Many systems now treat planning as a form of constraint satisfaction, exploiting new work on efficient algorithms in this area. These are just a few high points in a rich and very branchy history of planning systems. A good historical introduction to planning starts with an article in AI Magazine titled \" AI Planning: Systems and Techniques \" (Hendler et al. 1990). Beginning with a description of the planning problem as \" designing systems which can describe a set of actions (or plan) which can be expected to allow the system to reach a desired goal, \" Hendler et al. discuss common techniques used for planning, a chronology of planning systems, and some of the problems that planning addresses: reasoning about time, physical constraints on solutions, execution uncertainty, perception, and multi-agent systems. In addition to Hendler et al.'s discussion of …","PeriodicalId":8272,"journal":{"name":"Appl. Intell.","volume":"7 1","pages":"17-19"},"PeriodicalIF":0.0,"publicationDate":"2001-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75790588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Curriculum descant: pre-disciplinary AI","authors":"Deepak Kumar","doi":"10.1145/376451.376461","DOIUrl":"https://doi.org/10.1145/376451.376461","url":null,"abstract":"emphasize writing and critical-thinking skills. For instance, at Bryn Mawr college, we require all our incoming students to take two such courses, designated as College Seminars. I quote from the college's prospectus about a description of these courses: \" The College Seminars are discussion-oriented , reading-and writing-intensive courses for first-and second-year students. Topics (of these courses) vary from year to year, but all seminars are designed and taught by faculty from several different fields and are intended to engage broad, fundamental issues and questions. These courses have a predisciplinary rather than an interdisci-plinary intent: their aim is to revisit and revitalize questions that tend to be taken as settled by existing disciplines. Course materials include books and essays but also films, material objects, social practices, scientific observations and experiments. \" For more information on this program, and specific course description visit Inspired by sentiments expressed in the two pieces above, I would like to propose the creation of a pre-disciplinary writing intensive course that centers around the issues of artificial intelligence and philosophy of mind. Such a course can use a combination of materials taken from a selection of classic papers, videos of AI systems, movies (AI documentaries as well as Hollywood-style productions), and articles on AI as reported in the popular press. When team-taught by faculty from other disciplines , one quickly discovers an exciting array of readings that could be used to formulate the course content. I am also thinking of I n an earlier issue of this column, (\" Interdisciplinary AI, \" intelligence, Volume 11, Number 1, 2000) Richard Wyatt wrote: \" Artificial intelligence, as a course offered within computer science programs, should be an interdisciplinary course. Stated more carefully , the correct design for an undergraduate artificial intelligence course for a computer science department is such that it should be able to be taken by any student possessing good analytic skills but lacking programming skills. The interdisciplinary nature of a well-designed artificial intelligence course is not itself a goal of the preferred course design, but is a consequence of it. \" Computer science programs are not the ideal training grounds for artificial intelligence. There are of course exceptions, but in general, computer science students lack an understanding of philosophical issues. \" In short, artificial intelligence should be an interdisciplinary course and we, as instructors , should consciously conceive of it as such. \" If we ourselves …","PeriodicalId":8272,"journal":{"name":"Appl. Intell.","volume":"1 1","pages":"15-16"},"PeriodicalIF":0.0,"publicationDate":"2001-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88291832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Letter from the chair","authors":"J. Marks","doi":"10.1145/504313.504315","DOIUrl":"https://doi.org/10.1145/504313.504315","url":null,"abstract":"The current slate of ACM journals does not provide much outlet for AI research. So any proposal to start an ACM journal in an area of AI merits serious consideration. Just such a proposal is about to be made to the ACM Publications Board by Dr. Kishore Papineni of IBM' s T.J. Watson Research Center. Dr. Papineni is proposing a new journal, tentatively titled \" Transactions on Speech and Language Processing. \" I think that SIGART should give strong support to his proposal. The proposed journal will focus on the theory, design, development, and evaluation of practical systems that process human language in text or spoken form. The scope is intentionally broad: A subset of possible topics for papers includes natural language understanding, natural language generation, machine translation, document summarization, question-answer systems , speech recognition, speech generation, and audio indexing. Submitted papers will be subjected to reviewing standards typical for ACM journals. About 20 high-quality papers will be published per year, starting in 2003. Because of its broad coverage and its emphasis on practical methods and systems, the proposed journal differs significantly from existing journals such as \" Computational Linguistics, \" \" Natural Language Engineering, \" \" Machine Translation, \" \" Computer Speech and Language, \" IEEE' s \" Transactions on Speech and Audio Processing. \" And of course the new journal would carry the ACM imprimatur, which is useful to authors and readers alike as an implicit indicator of quality. If you have any thoughts on Dr. Papineni's proposal, I encourage you to share them with him (papineni@us.ibm.com) and with me (marks@merl.com). In future letters I will summarize any comments received and keep you apprised of future developments regarding the proposed journal. P.S. Chris Welty, the Editor-in-Chief of our magazine, lost a brother in the September 11th attack. Timothy Welty was a member of the New York City Fire Department and was in the World Trade Center when it collapsed. We offer our support and sympathy to Chris in these difficult days.","PeriodicalId":8272,"journal":{"name":"Appl. Intell.","volume":"310 1","pages":"5"},"PeriodicalIF":0.0,"publicationDate":"2001-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79956258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}