AI Magazine Volume 26 Number 4 (2006)(2005) (© AAAI) 25th Anniversary Issue

July 9; Biplav Srivastava and Jim Blythe, cochairs); Human Comprehen- The Workshop sible Machine Learning (held Saturday, July 9; Dan Oblinger, chair); Inference for Textual Question Answering (held Program at the Saturday, July 9; Sanda M. Harabagiu, chair); Integrating Planning into Scheduling (held Sunday, July 10; Mark Boddy, chair); Learning in Computer Twentieth National Vision (held Sunday, July 10; Bir Bhanu, chair); Link Analysis (held Sun- day, July 10; Dunja Mladenic, Natasha Conference on Milic-Frayling, and Marko Grobelink, cochairs); Mobile Workshop (held Wednesday, July 13, Sheila Tejada and Paul E. Rybski, cochairs); Modular Artificial Intelligence Construction of Human-Like Intelli- gence (held Sunday, July 10; Kristinn R. Thorisson, chair); Multiagent Learning (held Sunday, July 10; Eduardo Alonso, Diego Molla Aliod, Eduardo Alonso, chair); Question Answering in Restrict- ed Domains (held Sunday, July 10, Srinivas Bangalore, Joseph E. Beck, Bir Bhanu, Diego Molla Aliod, chair); Spoken Lan- Jim Blythe, Mark Boddy, guage Understanding (held Saturday, Amedeo Cesta, Marko Grobelink, July 9; Gokhan Tur (chair). Dilek Hakkani-Tür, Sanda M. Harabagiu, Alain Lege, Deborah McGuinness, Contexts and Ontologies: Stacy Marsella, Natasha Milic-Frayling, Theory, Practice, and Dunja Mladenic, Dan Oblinger, Paul E. Rybski, Applications Pavel Shvaiko, Stephen Smith, Biplav Srivastava, Pavel Shvaiko, Deborah McGuinness, Sheila Tejada, Hannes Vilhjálmsson, Holger Wache, and Alain Leger During the last decade, there was a se- Kristinn R. Thórisson, Gokhan Tur, ries of successful workshops and con- Jose Luis Vicedo, and Holger Wache ferences on the development and ap- plication of contexts and ontologies. Early workshops focused mostly on identifying what contexts and ontolo- gies are and how they can be formal- ized and exploited. More recently, with the emergence of distributed sys- tems (such as P2P systems and the se- ■ The AAAI–05 workshops were held on he AAAI–05 workshops were held mantic web), the focus has shifted to- Saturday and Sunday, July 9–10, in Pitts- on Saturday and Sunday, July ward issues of practical applications, burgh, Pennsylvania. The thirteen work- 9–10, in Pittsburgh, Pennsylva- shops were Contexts and Ontologies: T such as semantic integration, coordi- nia. The cochairs of the AAAI-05 Work- Theory, Practice and Applications, Edu- nation, and meaning negotiation cational Data Mining, Exploring Plan- shop Program were Adele Howe, Col- among information sources, where ning and Scheduling for Web Services, orado State University and Peter Stone, both contexts and ontologies were ap- Grid and Autonomic Computing, Hu- The University of Texas at Austin. The plied as promising solutions. Howev- man Comprehensible Machine Learn- fourteen workshops were Contexts and er, few, if any, of these meetings ing, Inference for Textual Question An- Ontologies: Theory, Practice and Appli- focused on combining the themes of swering, Integrating Planning into cations (held Saturday, July 9; Pavel ontologies and contexts and dis- Scheduling, Learning in Computer Vi- Shvaiko and Deborah McGuinness, cussing them as complementary disci- sion, Link Analysis, Work- cochairs); Educational Data Mining shop, Modular Construction of Human- plines. (held Sunday, July 10; Joseph E. Beck, like Intelligence, Multiagent Learning, This contexts and ontologies work- Question Answering in Restricted Do- chair); Exploring Planning and shop aimed to bring together people mains, and Spoken Language Under- Scheduling for Web Services, Grid and from the context and ontology com- standing. Autonomic Computing (held Saturday, munities and facilitate discussion

102 AI MAGAZINE Copyright © 2005, American Association for Artificial Intelligence. All rights reserved. 0738-4602-2005 / $2.00 25th Anniversary Issue about research and approaches to in- application perspectives. The founda- though computers enable collection of formation integration, thereby high- tions session covered some bridges be- keystroke level data, this level is prob- lighting different perspectives and tween contexts and ontologies in in- ably not the best one for classifying making the meeting of these commu- formation integration scenarios (such students or examining the data. One nities mutually beneficial. The work- as airfare and e-government). The lan- proposal was to encode special-case shop pushed the cross-fertilization and guage and reasoning session concen- detectors, such as an expert in the do- exchange of ideas (such as what are the trated on ambiguities of natural lan- main being able to realize that a par- commonalities and differences in the guage, encoding natural language into ticular characteristic must necessarily methods, which of the methods from a logical language, and the trade-off be exhibited, while a novice must per- the ontology community can be suc- between expressivity of logical lan- form several tests to confirm its exis- cessfully adopted in the context com- guages and reasoning. The informa- tence. Preprocessing log files with such munity, and vice versa, and what work- tion retrieval session focused on the is- detectors enables researchers to better ing definitions of terms enhance sues of semantic annotation, rele- classify students and understand how research progress). For example, one vance, and scoping of information de- they are learning. An alternate ap- perspective was that ontology can be pending on the application context. proach was to provide a generic tool viewed as an explicit encoding of a do- The ontology matching session intro- for browsing and summarizing stu- main model that may be shared and duced a few new approaches to the se- dent interactions with computer tu- reused. Another perspective is that a mantic heterogeneity problem using tors. This tool allows researchers to se- context can be viewed as an explicit the match operation. lect the level of detail they want to see encoding of a domain model that is ex- The poster and discussion and and avoids the problem of being un- pected to be local and may contain one wrap-up sessions generated many able to “see the forest for the trees.” party’s subjective view of the domain. fruitful discussions on the workshop Using students’ performance data Some technical themes discussed in themes. In particular, participants (how they solve problems) to con- the workshop include (1) approaches agreed that the main themes of con- struct a model of the domain produces to the semantic heterogeneity prob- vergence among contexts and ontolo- a very different result than asking do- lem using combinations of multiple gies are information interoperability main experts to construct such mod- contexts and ontologies; (2) technical and reuse. They also agreed that the els. This work focused on examining problems related to integration of con- workshop was productive and demon- student performance data, finding texts and ontologies from theoretical, strated a robust interest in a contexts questions with correlated perfor- practical, and application perspec- and ontologies workshop next year. mance, and then extracting factors tives. The workshop papers were pub- that describe the domain. Construct- The workshop consisted of two in- lished as an AAAI technical report and ing domain models in this way seems vited talks, four technical sessions, two posted in AAAI’s digital library. to result in many fewer factors to de- poster sessions, and a discussion and scribe a domain compared to expert beliefs. While hand-crafted domain wrap-up session. We received 30 sub- Educational Data Mining models are a useful theoretical descrip- missions: 11 were selected for techni- tion, students do not seem to perform cal sessions and 16 were selected for Joseph E. Beck or recognize differences at such a sub- poster sessions. The field of educational data mining tle level. In the first invited talk, Fausto focuses on improving our knowledge Although this workshop was the Giunchiglia from the University of of learning and teaching by extracting first one at AAAI, the quality of papers Trento, discussed how ontologies can patterns from the data collected as was strong, and we look forward to be contextualized, thereby yielding part of the educational process. Com- having a second such workshop at contextual ontologies, which have the puters, especially computer tutors, en- AAAI 2006 in Boston. advantages of both ontologies and con- able data collection over long periods The workshop papers were pub- texts. In the second invited talk, Chris of time, for many students, and at a lished as an AAAI technical report and Welty of IBM discussed why ontologies fine time scale. These advantages pro- posted in AAAI’s digital library. need contexts and why contexts need vide a novel source of data for under- ontologies. He also considered some standing how students learn. Al- outbriefing from the Advanced Re- though there have been similar Exploring Planning and search and Development Activity (AR- workshops, those workshops were lim- Scheduling for DA) Interoperable Knowledge Repre- ited to specialized conferences. There- sentation for Intelligence Support fore, one goal of this workshop was to Web Services, Grid, and (IKRIS) program on contexts and what bring together a broader group of AI Autonomic Computing may be useful to include concerning researchers. them in knowledge representation lan- Two big ideas cut across several Biplav Srivastava and Jim Blythe guages for interoperability. workshop talks: Educational data can Planning and scheduling, long active Technical sessions addressed various be very fine-grained, and we need areas of research, have recently re- combinations of contexts and ontolo- some means of “stepping back” to ceived increasing attention for their gies from theoretical, practical, and view an aggregation of the data. Al- role in managing workflows on the

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Web and on computational grids, en- be located centrally or distributed would under the same conditions. Ma- compassing workflow generation, across a network, has emerged as the chine learning has also been widely storage and retrieval, analysis, compo- biggest challenge in reducing the cost used to support credit approval deci- sition, allocation of resources, execu- of information technology while in- sions, yet banks are becoming increas- tion, and repair. The appropriate use of creasing business productivity. Self- ingly responsible for explaining the these technologies will have enor- management of systems for configura- reasons behind a denial of credit. Au- mous significance for scientific appli- tion, protection, recovery, and tonomic systems are beginning to em- cations and business process integra- optimization comes under the ambit ploy machine learning to support tion. Two successful workshops were of autonomic computing and similar common administrative policies, yet held at ICAPS 2003 and 2004 on plan- initiatives in industry. Here, workflows system administrators are reluctant to ning and scheduling for Web and grid have been adopted as the underlying trust automated technology they do services. This year, we recognized the representation to connect interrelated not understand. need to bring the discussions to a tasks required for self-management. The workshop’s ten presentations wider AI audience and also extended Gerry Tesauro from IBM Research gave addressed comprehensibility from the scope to self-management of re- an invited talk on autonomic comput- three perspectives. sources (that is, autonomic comput- ing in which he presented an overview First, several of the more senior ing). of the system self-management prob- learning researchers offered their per- The workshop was held in three ses- lem. He related that his group has sonal overview of the last 20 years of sions corresponding to the three appli- found that learning-based (nonmodel) learning research on comprehensibili- cation areas—web services, grid, and approaches can have comparable per- ty. Pat Langley and Michael Pazzani autonomic computing. In the web ser- formance to model-based approaches described a range of their work and vices session, Marco Pistore from the for resource allocation in distributed provided good overviews of how it re- University of Trento gave an invited systems, enabling good performance lated to other’s work in comprehensi- talk on automatic composition of exe- without requiring in-depth system bility. cutable web services with a case study model information. Second, several researchers present- on its use for integrating complex Overall, the workshop was success- ed frameworks that improved compre- business processes. We also had papers ful in generating thoughtful discus- hensibility for known learning algo- on qualitatively evaluating Web ser- sions and building a broad under- rithms in some way. For example, vices composition approaches, learn- standing of the challenges ahead. John Burge provided a pair of metrics ing to induce source descriptions and The workshop papers were pub- for dynamic Bayes nets and showed matching of services, and interesting lished as an AAAI technical report and how each provided learned nets with a ideas on composition and enactment posted in AAAI’s digital library. specific meaning for the user. Flavian approaches. In the ensuing discus- Vasile provided an extension to RIP- sions, it emerged that a key challenge PER that produces more comprehensi- in using planning and scheduling for Human Comprehensible ble rules. Pedro Domingos provided a web services is the formulation of the Machine Learning Markov logic network as a basis for realistic problem and this often leads comprehensible machine learning. to interesting new techniques for ad- Dan Oblinger A third type of presentation focused vancing the field. Humans need to trust that intelligent on comprehensibility in specific do- Presentations in the grid session de- systems are behaving correctly, and mains or for specific applications. For scribed a formal framework to model one way to achieve such trust is to en- example, Rich Caruana looked at how the scheduling problem for grids, the able people to understand the inputs, understanding or misunderstanding use of techniques developed for dis- outputs, and algorithms used, as well of induced models in the medical field tributed agents, and an architecture as any new knowledge acquired has its own particular nuances. for developing distributed data min- through learning. As the use of ma- Some attendees and presenters were ing applications. As in the previous chine learning increases in critical op- from allied fields. For example, Si- session, authors focused more on erations, it is being applied increasing- mone Stumpf looked at comprehensi- managing realistic systems and expos- ly in domains where the learning bility from a human-computer inter- ing their underlying assumptions, and system’s inputs and outputs must be action (HCI) perspective, and Noboru less on specific planning or scheduling understood or even modified by hu- Matsuda discussed learning as an au- algorithms. The papers also shared the man operators. For instance, e-mail thoring tool for cognitive tutoring sys- idea that the tasks of workflow alloca- classification systems may need to tems. tion and repair are likely to be dis- gain the user’s trust by explaining A panel of five speakers guided a tributed across different hosts rather their predictions in a language the us- lively discussion on open research is- than centralized. Both these trends er can understand. Intelligent office sues in comprehensibility. Topics for mark interesting departures from the assistants learn from a user’s prefer- the discussion were solicited before previous workshops held at ICAPS. ences and behavior, but if an agent is and during the workshop. There was a Management of resources, includ- to be useful, its users must trust that it general sense of surprise among the ing software and hardware that may will make the same decisions that they participants that the issues being

104 AI MAGAZINE 25th Anniversary Issue raised were of broad interest to the lutions discussed will further improve the same treatment, with the roles for community. such systems and enable them to tack- each community reversed. However, The degree of interaction and inter- le more complex questions. the several papers that did address the est from both audience and presenters The workshop papers were pub- integration we are seeking were uni- suggests that this is a fertile area for lished as an AAAI technical report and versally seen as relevant, and discus- follow-up forums. posted in AAAI’s digital library. sion at the 2004 workshop itself led to The workshop papers were pub- a more integrated view. At the work- lished as an AAAI technical report and shop’s conclusion, it was commonly posted in AAAI’s digital library. Integrating Planning acknowledged that there is a wide va- into Scheduling riety of possible integrations of plan- ning and scheduling, in some cases in- Mark Boddy, Amedeo Cesta, Inference for Textual volving adding limited forms of and Stephen Smith Question Answering resource reasoning to planning. The topic of the workshop was how to At the 2005 workshop, several pa- Sanda M. Harabagiu integrate planning capabilities with pers advanced the themes identified The workshop on inference for textual scheduling algorithms and frame- and discussed at the 2004 workshop, question answering provided a forum works. In recent years, the AI planning while others highlighted an area that for researchers involved in studying community has focused increasingly received little attention last year: inte- various forms of reasoning used in on extending classical planning for- grated planning and scheduling for question-answering systems. When malisms to incorporate notions of re- distributed systems. The summary sources and time. Recently published reasoning about a question and a can- panel and discussion concluded that work and the results achieved in the didate answer, an inference engine us- collectively the two workshops have most recent International Planning es two forms of knowledge: (1) knowl- yielded a sufficient understanding of Competition (IPC) at ICAPS 2004, edge derived only from the question both kinds of integration strategies, have demonstrated considerable and the candidate answer, and (2) and the domain characteristics for progress on incorporating metric world knowledge extracted from vari- which those strategies are likely to be quantities and durative actions into ous ontologies and knowledge data- useful, to provide a general overview the classical planning framework, in- bases. Several examples of inference and a preliminary synthesis. The cur- creasing the relevance of classical methods used for solving complex rent intent is to write up these insights planning techniques to scheduling questions were presented: abductive for publication. We also reached a gen- problems. However, because the focus reasoning, default reasoning, and in- eral consensus that a more appropriate in classical planning is on individual ference based on epistemic logic or de- actions, rather than organizing or syn- term to describe work in this area scription logic. Language interpreta- chronizing with operations in the larg- would be “integrating planning and tion also requires its own forms of er environment, and on discrete state scheduling.” inference, such as conversational im- changes, rather than multiple, inter- The workshop papers were pub- plicatures, processing of metonymies, acting asynchronous processes, aug- lished as an AAAI technical report and and metaphors. Inferring the answer menting planning systems with mod- posted in AAAI’s digital library. to a question is often constrained by els that include durative actions and temporal and spatial reasoning. resource capacity constraints is unlike- Learning in The challenge issued by this work- ly by itself to be an effective solution shop was to find a suitable knowledge for problems in which resource alloca- Computer Vision representation and a robust inference tion is central. On the other hand, the Bir Bhanu mechanism that handles a majority of techniques schedulers typically use to the ambiguities generated by natural solve embedded planning problems Computer vision was one of the first texts. This problem is of interest for tend to be problem-specific and are areas that the AI community worked both the natural language processing difficult to extend and transfer to new on, and now the two communities (NLP) community and the knowledge contexts. (learning and computer vision) are representation and reasoning (KRR) The 2005 workshop was a follow-up marching along their own paths with community. The workshop was an ex- to the workshop on the same topic little interaction. The objective of the cellent opportunity for researchers held at ICAPS 2004. At the previous first one-day workshop on learning in from both areas to meet and discuss workshop, the differences in perspec- computer vision was to bring the two this problem. The talks highlighted in- tive on this integration issue were evi- communities together to address in- ference mechanisms based on very dif- dent from the outset. terdisciplinary research issues. Such an ferent knowledge representations and Planning-centric papers received interaction would help increase the operating on different text collections. good reviews from people with strong competence of AI vision systems to be The workshop helped foster solutions roots in the planning research com- used in complex real-world applica- to problems in several intelligent ques- munity and were deemed irrelevant by tions. tion and answer systems that can now scheduling researchers. Papers with a The goal of computer vision research justify their extracted answers. The so- very strong scheduling focus received is to provide computers with human-

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like perception capabilities so that they ing, relational data mining, and, more The discovery of link structure and can sense the environment, under- generally, data mining. Typical exam- exploitation of graph properties is be- stand the sensed data, take appropriate ples are in the areas of trend analysis, coming a common trend in informa- actions, and learn from this experience community identification, web user tion retrieval. A paper on topic-specific to enhance future performance. The profiling, media clipping, and market- scoring of documents combined the computer vision field has evolved from ing, where link analysis complements standard methods with link properties the application of classical pattern other research fields and derives addi- of the topics structure to enhance doc- recognition and image-processing tional value from information process- ument retrieval. Similarly, a paper on techniques to advanced applications of ing. Another interesting scenario is the summarization of broadcast news image understanding, model-based vi- extraction of information from un- video exploited the link analysis of sion, knowledge-based vision, and sys- structured data, representation of the named entities. Because these and re- tems that exhibit learning capability. extracted data in graphical form, and lated techniques can be boosted by the The ability to reason and the ability to further analysis of the resulting graph availability and quality of a domain learn are the two major capabilities as- structure to derive and discover new ontology, the issue of automatic ex- sociated with these systems. In recent knowledge. traction and structuring of domain- years theoretical and practical ad- This workshop followed a series of specific terms is of great importance. vances have been made in the field of text mining and link analysis work- The workshop included a paper on a computer vision by new techniques shops that we have organized over the graph-based ranking algorithm that and processes of learning, representa- last 15 years at main international identifies domain keywords and ex- tion, and adaptation. Learning repre- conferences, including the Interna- ploits the dependencies among terms sents the next challenging frontier for tional Conference on Machine Learn- to structure them as concepts and at- computer vision. ing (ICML), the Knowledge Discovery tributes. Applications often challenge During the workshop there was a and Data Mining Conference (KDD), the standard research methods; for ex- discussion of the development of flex- the IEEE International Conference on ample, the application of relational ible, robust AI-based computer vision Data Mining (ICDM), and the Interna- graphs analysis to the problem of de- systems for real-world dynamic scene tional Joint Conference on Artificial tecting tax fraud illustrates a prototype understanding. There were talks on Intelligence (IJCAI) (see http://kt.ijs.si/ that has been deployed in practice. learning in computer vision, multi- dunja/TextWebJSI/). The workshop papers were pub- robot interaction, sensor planning, in- Presentations at this workshop cov- lished as an AAAI technical report and cremental 3D modeling, semantic fea- ered a range of topics, attesting to the posted in AAAI’s digital library. ture extraction from video, richness and versatility of this research recognizing activities in video, sensori- area. Methods for manipulation of Mobile Robot Workshop motor learning, visually guided con- graphs were covered in several papers, trol, and statistical learning. including research on pattern match- Sheila Tejada and Paul E. Rybski The workshop papers were pub- ing efficiency of semantic graphs using The mobile robot workshop was an ex- lished as an AAAI technical report and higher-order constructs and extraction tension of the AAAI 2004 robot pro- posted in AAAI’s digital library. of relevant semantic subgraphs to fa- gram centered around the theme cilitate learning using Bayesian net- “ Interacting with Humans.” Link Analysis works. Data analysis workflows gener- Participants from the robot competi- ally include a variety of tools to solve tion and exhibition presented high- Dunja Mladenic, Natasha Milic- a problem. Graph analysis is just one lights of their work at the workshop. Frayling, and Marko Grobelink of the components typically used. As The robot program included three Link analysis has been developed over expected, different application areas competitions—the robot challenge, a the past 20 years in various fields, in- impose different types of workflow for scavenger hunt, and an open interac- cluding discrete mathematics (graph analysts, and thus the tools need to be tion task—as well as a general robot theory), social sciences (social network flexible. This was addressed by specify- exhibition. analysis), and computer science (graph ing a representation language to en- The robot challenge task was to de- as a data structure). Recently this area able exchange of patterns, hypotheses, velop a robot that can attend the con- has attracted wider attention for its ap- and evidence among analysis tools. ference. This task included a number plicability in areas such as law enforce- The workshop included several pa- of subtasks: finding the registration ment investigations (terrorism and pers that show cross-application bene- desk from the entrance to the confer- money laundering), fraud detection fits. For example, one applied the re- ence center, registering for the confer- (insurance and banking), web analysis sults of social networks research to the ence, performing volunteer duties as (search engines and marketing), and problem of ranking autonomous sys- required. LABORIUS, from the Univer- telecommunications (routers, traffic, tems on the Internet. Another ad- sité de Sherbrooke led by François and connectivity). Particularly interest- dressed the management of servers Michaud, earned first place for their ing are problems and issues that fall based on the power law relationships work on Spartacus. Spartacus exhibit- within the intersection of link analysis observed in the network topologies ed an impressive variety of algorithms and fields such as Web and text min- themselves. in a motivated behavior architecture

106 AI MAGAZINE 25th Anniversary Issue to perform the navigation and pro- following teams earned honorable of multimodal dialogue planners. cessing of visual and auditory inputs mention: the Carnegie Mellon Univer- Among the theoretical papers present- required for high-level interaction. sity Pink Team, the Drexel University ed was a proposal by Alexei V. Sam- Participants in the scavenger hunt Autonomous Systems Lab, Kansas sonovich and Kenneth A. De Jong to were given a list of objects that would State University, the Stony Brook use neural networks on top of symbol- be in specified locations at specified Robot Design Team, the Carnegie Mel- ic representations to learn groupings times. The task required robots to map lon University CMDash’05, and the and allow the system to evolve over and navigate a dynamic area with University of Pittsburgh. time. Another was Zippora Arzi- moving obstructions, such as people, The workshop papers were pub- Gonczarowski’s ISAAC, with a special to acquire the desired objects. This lished as an AAAI technical report and module construct that allows incre- task was designed to use some of the posted in AAAI’s digital library. mental, compositional system growth. same capabilities as urban search-and- Many of the implemented systems rescue robots. The panel of judges Modular Construction of presented were formidable attempts at awarded first place to the Harvey large-scale integration. For example, Mudd College robot, HMC Hammer. Humanlike Intelligence the MARCO system by Matt MacMa- The team of undergraduates used an hon, a system for following route in- Kristinn R. Thórisson, Hannes Evolution ER1 robot with relatively in- Vilhjálmsson, and Stacy Marsella structions, addresses shortcomings of expensive equipment in a robot-as- the multicomponent GRACE and computer-peripheral design that suc- From the birth of AI, one of the central GEORGE robots (AAAI Robot Chal- cessfully found objects in a very challenges of the field has been to un- lenge 2002). A robot designed by challenging environment. derstand and model human intelli- Maren Bennewitz, Felix Faber, Do- gence. The primary motivation for The open interaction event encour- minik Joho, Michael Schreiber, and this workshop was the belief that aged researchers to demonstrate tech- Sven Behnke, can maintain dialogue meeting that challenge requires not niques for interactive, entertainment, with two humans at once and the ar- only studying many separate skills but and social . Participants in the chitecture created by Nikolaos Mav- also integrating them into a coherent competition were encouraged to de- ridis and Deb Roy enables a robot to whole. In particular, the development sign robots that grabbed and sustained interact with a user through speech, of machines that collaborate and in- attendees’ attention. Hanson Robotics updating its beliefs about the sur- teract socially with people necessitates won the competition for their human roundings using a range of heteroge- integration of numerous complex emulation robot, an that de- neous perceptual inputs. Addressing technologies. This integration in turn picted the late science fiction writer somewhat different questions, a robot requires better tools and an increased Phillip K. Dick. The Hanson Robotics built by Jesse Gray and Cynthia focus on architecture. team showed that a robot with a very Progress toward these goals is best Breazeal runs simulations of people to human face could interact well with ensured by a healthy balance between infer their mental state. people and not be viewed as disturb- theory, tools, and implementation. In- There is significant potential for col- ing. deed, the papers presented at the laboration in the research presented. The robot exhibition was designed workshop fell roughly equally into The theoretical work needs to be test- to showcase current research that does these three categories. Some tools pre- ed in context—some of the robot ar- not strictly fit any of the competition sented took the form of specifications chitectures, such as Mavridis and tasks. The following teams earned and software libraries. Examples are Roy’s, could provide that test bed. Eric technical achievement awards: LABO- OpenAIR, developed by MINDMAK- Baumer and Bill Tomlinson’s work on RIUS for work on map building and ERS.ORG, and NetP by Kai-Yuh Hsiao, synthetic social construction could human-robot interaction; Harvey Peter Gorniak, and Deb Roy. Both are quite possibly benefit from Vilhjalms- Mudd College for overall excellence in geared toward building complex soft- son and Marsella’s work on social a fully autonomous system; University ware systems and proposing methods communication or Andrew Gordon’s of Massachusetts Lowell for control in- for easier connection of programming classification of cognitive architec- terface usability and robust path find- languages and platforms. tures. Rakesh Gupta and Ken Henna- ing and object recognition; Carnegie Among other tools were the white- cy’s work on commonsense reasoning Mellon University for a vi- boards by Kristinn Thorisson, Thor provides an interesting piece to the sionary hardware concept; a Naval Re- List, Christopher Pennock, and John puzzle of designing robots to work ef- search Laboratory collaboration with DiPirro, which provide semantic pub- fectively indoors. All of the work pre- University of Missouri for engaging in- lishing, subscribing, and routing of sented, especially the multimodule teraction using a cognitive model and messages and streams. Thor List and robot architectures, could benefit from innovative interface; the Swarthmore his collaborators showed how modu- using OpenAIR and NetP, which College Academic Autonomy team for larity can be brought to the construc- would simplify integration and ease adaptive vision for lighting condi- tion of vision architectures, while module reuse. tions; and the Carnegie Mellon Uni- Hannes Vilhjalmsson and Stacy During the AAAI conference our versity Tekkotsu project for visualiza- Marsella proposed common represen- workshop got a nice boost “from tion for education robots. The tations for enabling easy construction above”: Both Marvin Minsky’s

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works following game theory ap- Spoken Language proaches and others. Techniques var- ied from reinforcement learning to Understanding For information on 2006 evolutionary algorithms. Presenta- AAAI Workshops, please Gokhan Tur, Dilek Hakkani-Tür, and tions included an invited talk entitled Srinivas Bangalore visit: “Learning for Multiagent Decision Natural language processing (NLP) has Problems” by Geoff Gordon from the been one of the defining subtopics of www.aaai.org/ Center for Automated Learning and AI since its early days. In recent times, Workshops/2006 Discovery at Carnegie Mellon. NLP has predominantly been about The workshop papers were pub- text understanding and building asso- lished as an AAAI technical report and ciated resources for the purposes of in- posted in AAAI’s digital library. formation extraction, question an- keynote address and Ronald J. Brach- swering, and text mining. Many of man’s presidential address emphasized Question Answering in these tasks have nourished the cre- integration and large-scale modeling ation and development of extensive and urged the field to set its sights on Restricted Domains ontologies, practical semantic repre- human intelligence. Practically all of Diego Molla Aliod and Jose Luis Vicedo sentations, and novel machine-learn- the researchers in our workshop do so. ing techniques. We find this very exciting and hope Early question-answering systems of In a spirit similar to the workshop at they make real progress fast. the 1960s and 1970s were based on the Human Language Technology The workshop papers were pub- handcrafted databases and knowledge Conference / North American chapter lished as an AAAI technical report and systems of very specific domains, such of the Association for Computational posted in AAAI’s digital library. as the analysis of lunar rock samples Linguistics (HLT-NAACL) 2004 on this from the Apollo missions or of U.S. topic, our attempt was to broaden the Multiagent Learning baseball league statistics. In those days scope of language understanding to the choice to use restricted domains include spoken language understand- Eduardo Alonso was made out of necessity. Now theo- ing (SLU) in the context of applica- retical advances in AI and natural lan- When designing agent systems, it is tions such as speech mining and hu- guage processing (NLP), together with impossible to foresee all the potential man-machine interactive spoken increases in computing power and the situations an agent may encounter dialogue systems. We tried to bring to- availability of corpora and linguistic and specify an optimal agent behavior gether techniques that address the is- tools and resources, have enabled the in advance. Agents therefore have to sue of robustness of SLU to speech development of open-domain ques- learn from and adapt to their environ- recognition errors, language variabili- tion-answering systems. However, re- ment. This task is even more complex ty, and dysfluencies in speech with is- when nature is not the only source of stricted domains provide an interest- sues of semantic representation that uncertainty, and the agent is situated ing mix of challenges and opportu- provide greater portability to a dia- in an environment that contains other nities that have yet to be fully ex- logue model. We believe spoken lan- agents with potentially different capa- plored. For example, the limited data guage understanding is an especially bilities, goals, and beliefs. Multiagent available makes it difficult to apply attractive topic for cross-fertilization learning, that is, the ability of agents current question-answering tech- of ideas between the AI, information to learn how to cooperate and niques based on data redundancy, and retrieval (IR), NLP, speech, and seman- compete, becomes crucial in such do- generic lexical resources do not cover tic Web communities. We thank Dr. mains. the specific terminology of some do- Alexander I. Rudnicky, from the The workshop on multiagent learn- mains. On the other hand, some re- School of Computer Science at Carne- ing held July 10 as part of the AAAI stricted domains (such as the clinical gie Mellon University for accepting 2005 Conference in Pittsburgh domain) have high-quality, compre- our invitation to share his group’s achieved all its goals: It increased hensive ontologies and resources that work on spoken language understand- awareness and interest in adaptive can be used for high-precision ques- ing. agent research, encouraged collabora- tion-answering tasks. Following the We thank the program committee tion between machine learning and 2004 Association of Computational members for their informative reviews agent system experts, and gave a repre- Linguistics (ACL) workshop on ques- of the submitted papers. We thank the sentative overview of current research tion answering in restricted domains, authors for electing to present their in the area of adaptive agents. this one-day AAAI workshop explored work at this forum. And we thank the The workshop was an inclusive fo- some of the issues involved in this in- AAAI for inviting us to organize this rum for discussion about ongoing or creasingly active area of research and follow-up workshop. . completed work in both theoretical development. The workshop papers were pub- and practical issues. In particular, work The workshop papers were pub- lished as an AAAI technical report and was presented about learning to com- lished as an AAAI technical report and posted in AAAI’s digital library. municate and to get organized in net- posted in AAAI’s digital library.

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