UNITED STATES PATENT AND TRADEMARK OFFICE
`
`_____________________________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`_____________________________
`
`GOOGLE LLC,
`Petitioner,
`
`v.
`
`VOCALIFE LLC,
`Patent Owner.
`
`_____________________________
`
`Case No. IPR2022-00005
`U.S. Patent No. RE48,371
`_____________________________
`
`DECLARATION OF SIMON BRIÈRE
`
`Page 1 of 136
`
`GOOGLE EXHIBIT 1022
`GOOGLE v. VOCALIFE
`IPR2022-00005
`
`

`

`Declaration of Simon Brière
`
`I, Simon Brière, declare as follows:
`
`1.
`
`I make this declaration based on my own personal knowledge and, if
`
`called upon to testify, would testify competently to the matters contained herein.
`
`2.
`
`I am the lead author of a paper entitled, “Embedded and Integrated
`
`Audition for a Mobile Robot” (“the paper” or “my paper”). I have reviewed
`
`Exhibit 1009 in this proceeding, which is a true and accurate copy of the paper.
`
`3.
`
`I personally presented the paper at the American Association for
`
`Artificial Intelligence (“AAAI”) 2006 Fall Symposia Series. Specifically, I
`
`presented the paper at one of the eight symposia that was part of this series,
`
`entitled “Aurally Informed Performance: Integrating Machine Listening and
`
`Auditory Presentation in Robotic Systems” (below, I refer to this particular
`
`symposium as the “AAAI 2006 Fall Symposium”). The AAAI 2006 Fall
`
`Symposium was held at the Hyatt Regency Crystal City in Arlington, Virginia on
`
`October 13-15, 2006. Copies of the paper were distributed and available to the
`
`attendees of the AAAI 2006 Fall Symposium.
`
`4.
`
`The AAAI is, and was in 2006, a well-known technical organization
`
`that focuses on various aspects of research related to artificial intelligence. Every
`
`year for over two decades, the AAAI has held Fall Symposia and Spring Symposia.
`
`See https://aaai.org/Symposia/symposia.php. Those symposia, which are open to
`
`both AAAI members and nonmembers, provide a venue for researchers and
`
`1
`
`Page 2 of 136
`
`

`

`Declaration of Simon Brière
`
`educators to share ideas and learn from each other’s research in fields related to
`
`artificial intelligence (“AI”). Id. The papers presented at the symposia are
`
`published in the AAAI Conference proceedings. Id.
`
`5.
`
`The AAAI’s conferences and symposia were well-known events for
`
`those practicing in fields related to AI, including the related fields of aural/acoustic
`
`performance and machine listening, which was the subject of the AAAI 2006 Fall
`
`Symposium at which I presented the paper. The AAAI 2006 Fall Symposium was
`
`advertised in many places, including on the AAAI website in a “Call for
`
`Participation” that was distributed prior to the May 1, 2006 submission deadline
`
`for papers. A true and accurate copy of the Call for Participation is attached to this
`
`declaration as Appendix A.
`
`6.
`
`The Call for Participation for the AAAI 2006 Fall Symposium
`
`explained that “[t]he purpose of this symposium is to gather together researchers in
`
`machine listening, speech systems, and general robotics, as well as those in other
`
`disciplines, including AI, neuroscience, and the cognitive and social sciences, who
`
`are interested in a collaborative, interdisciplinary exploration of the range of issues
`
`that concern aurally informed performance in robots.” App’x A at 3. It therefore
`
`sought submissions “that describe computational approaches to aurally informed
`
`performance . . . .” App’x A at 3. At the suggestion of my thesis advisor, François
`
`Michaud, who is also a co-author on the paper, we submitted the paper in response
`
`2
`
`Page 3 of 136
`
`

`

`Declaration of Simon Brière
`
`to this Call for Participation. The paper was selected for presentation and included
`
`in the course materials of the AAAI 2006 Fall Symposium.
`
`7.
`
`The Call for Participation confirms that “registration information will
`
`be available on the AAAI website in July 2006.” App’x A at 2. Similarly, the
`
`Registration document distributed by AAAI via its website, a true and accurate
`
`copy of which is attached as Appendix B, provided both a link and a physical
`
`address to register for the symposium. App’x B at 2. I registered for the
`
`symposium via the AAAI website. The registration form shows that both AAAI
`
`members and nonmembers could register for the symposium, which is consistent
`
`with my recollection. App’x B at 13. Likewise, the Call for Participation explains
`
`that each symposium would include up to 40-60 participants, and that “active
`
`participants as well as a limited number of interested individuals on a first-come,
`
`first served basis” were allowed to join each symposium. App’x A at 2.
`
`8.
`
`The AAAI 2006 Fall Symposium at which I presented the paper was
`
`attended by approximately 20-30 attendees. Because this symposium was directed
`
`to “Aurally Informed Performance: Integrating Machine Listening and Auditory
`
`Presentation in Robotic Systems” as the subtitle indicates, it was attended by
`
`technical people who were skilled in the art of artificial auditory and acoustic
`
`technology. I recall the names of certain attendees, including Cindy Bethel,
`
`Frederick Heckel, and Derek Brock. Each of the attendees of the AAAI 2006 Fall
`
`3
`
`Page 4 of 136
`
`

`

`Declaration of Simon Brière
`
`Symposium received a copy of my paper, as well as copies of the other papers
`
`presented at the AAAI 2006 Fall Symposium.
`
`9.
`
`The AAAI likewise published an article discussing the AAAI 2006
`
`Fall Symposium in a Volume 28, Issue 1 of AI Magazine, in 2007. A true and
`
`accurate copy of that article is attached as Appendix D. AI Magazine is published
`
`by the AAAI and is sent to AAAI members. I received a copy of Volume 28, Issue
`
`1 of AI Magazine in 2007 and recall reading the article, which discusses the paper
`
`and my presentation of it:
`
`The final day opened with a brief look at research involving audition and
`
`speech in developmental robotics and concluded with two talks on recent
`
`work with integrated robotic auditory interaction systems. The first
`
`described the integration of real-time auditory processing hardware
`
`capable of localizing, separating, and tracking several simultaneous
`
`speech sources with a dialogue manager on a mobile robot. The other
`
`described work on the problem of recognizing which agent is being
`
`addressed in a spoken dialogue system involving multiple human and
`
`robotic speakers and hearers being developed for future planetary ground
`
`exploration missions.
`
`App’x C at 5 (emphasis added).
`
`4
`
`Page 5 of 136
`
`

`

`Declaration of Simon Brière
`
`10. The article further explains, consistent with my recollection, that the
`
`“[p]apers contributed to the symposium are available as Technical Report FS-06-
`
`01 from AAAI Press.” App’x C at 5. An excerpt from the cover pages of Technical
`
`Report FS-06-01 is attached as Appendix D. The table of contents lists my paper.
`
`App’x D at 7.
`
`11.
`
`I have also cited to my paper in other publications, including in a
`
`paper entitled “Embedded Auditory System for Small Mobile Robots,” which I
`
`presented at the 2008 IEEE International Conference on Robotics and Automation
`
`in Pasadena, California in May 2008. A true and accurate copy of that paper is
`
`attached as Appendix E. See App’x E at 6 (note [4]). Likewise, I cited to my paper
`
`in my 2007 dissertation. A true and correct copy of my dissertation is attached as
`
`Appendix F. See App’x F at 75 (note [4]).
`
`12.
`
`I am being compensated for my time at my usual and customary rate
`
`of $225 per hour. However, no part of my compensation depends on the outcome
`
`of this proceeding, and I have no other interest in this proceeding.
`
`
`
`
`
`5
`
`Page 6 of 136
`
`

`

`Declaration of Simon Brière
`
`I declare that all statements made herein of my own knowledge are true and
`
`that all statements made on information and belief are believed to be true; and
`
`further that these statements were made with knowledge that willful false
`
`statements and the like so made are punishable by fine or imprisonment, or both,
`
`under Section 1001 of Title 18 of the United States Code.
`
`
`
`
`Executed on March 1, 2022 in Sherbrooke, Quebec.
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`_________________________
`
`Simon Brière
`
`6
`
`Page 7 of 136
`
`

`

`APPENDIX A
`APPENDIX A
`
`Page 8 of 136
`
`Page 8 of 136
`
`

`

`Call for Participation
`
`2006 AAAI Fall
`Symposium Series
`
`October 13‒15, 2006  Hyatt Regency Crystal City, Arlington, Virginia
`
`Sponsored by the American Association for Artificial Intelligence
`
`With support from the Naval Research Laboratory
`
`445 Burgess Drive, Menlo Park, California 94025 650-328-3123 650-321-4457 (fax) www.aaai.org/Symposia/Fall/2005/
`
`Page 9 of 136
`
`

`

`Important Deadlines
`
`May 1, 2006: Submission due to organizers
`
`May 22, 2006: Notifications of acceptance sent by organizers
`
`August 31, 2006: Accepted camera-ready copy due to AAAI.
`
`Web Site
`www.aaai.org/Symposia/Fall/fss06symposia.php
`
`Photo courtesy Arlington Convention and Visitors Bureau
`
`2 AAAI FALL SYMPOSIA
`
`The American Association for Artificial In-
`
`telligence is pleased to present the 2006
`Fall Symposium Series, to be held Friday
`through Sunday, October 13–15 at the Hyatt Re-
`gency Crystal City in Arlington, Virginia. The
`symposium series is sponsored by the American
`Association for Artificial Intelligence, with sup-
`port from the Naval Research Laboratory. The ti-
`tles of the eight symposia are:
`
` Aurally Informed Performance: Integrating
`Machine Listening and Auditory Presenta-
`tion in Robotic Systems
` Capturing and Using Patterns for Evidence
`Detection
` Developmental Systems
` Image Comprehension
` Integrating Logical Reasoning into Everyday
`Applications
` Interaction and Emergent Phenomena in So-
`cieties of Agents
` Semantic Web for Collaborative Knowledge
`Acquisition
` Spacecraft Autonomy: Using AI to Expand
`Human Space Exploration
`
`Symposia will be limited to 40-60 participants
`each. Participation will be open to active partici-
`pants as well as a limited number of interested in-
`dividuals on a first-come, first-served basis. Reg-
`istration information will be available on the
`AAAI web site in July 2006.
`
`Submission Requirements
`Interested individuals should submit a paper or
`abstract by the deadline listed below. Please mail
`your submissions directly to the chair of the indi-
`vidual symposium according to their directions.
`Do not mail submissions to AAAI.
`
`For full descriptions and submission instructions,
`please consult the AAAI Fall Symposium Web site
`and the supplementary symposia pages, or con-
`tact:
`
`American Association for
`Artificial Intelligence
`445 Burgess Drive, Suite 100
`Menlo Park, California 94025 USA
`Telephone: 650-328-3123
`Fax: 650-321-4457
`E-mail: fss06@aaai.org
`
`Page 10 of 136
`
`

`

`Aurally Informed Performance:
`Integrating Machine Listening and Auditory Presentation in Robotic Systems
`
`AAAI FALL SYMPOSIA 3
`
`Submissions
`Prospective participants are invited to submit a
`research abstract or a position paper. Submis-
`sions that describe computational approaches to
`aurally informed performance and/or, empirical
`results, work-in-progress, speculative approach-
`es, and theoretical issues that bear on the topic are
`all encouraged. Papers are to be two to six pages
`in length and must be submitted by e-mail in
`PDF format to derek.brock@nrl.navy.mil with
`the phrase “FSS06-submission” in the subject
`line.
`
`Organizing Committee
`Derek Brock (cochair), Naval Research Laborato-
`ry (derek.brock@nrl.navy.mil); Ramani Du-
`raiswami (cochair), University of Maryland (ra-
`mani@umiacs.umd.edu); and Alexander I. Rud-
`nicky (cochair), Carnegie Mellon University
`(alex.rudnicky@cs.cmu.edu).
`
`Robots designed to function as appliances
`
`and human surrogates in public and pri-
`vate settings are already being moved from
`research projects to fully deployed systems. In
`keeping with the goals of intuitive human-robot
`interaction, many of these platforms incorporate
`rudimentary speech communication interfaces,
`and others are engineered for specific types of lis-
`tening tasks. Even so, aurally informed behaviors
`in robots, and their integration with other per-
`ceptual and reasoning systems, remain far behind
`the broad and mostly transparent skills of human
`beings.
`
`Part of the problem is that while much is
`known about the human physiology of listening,
`much less is understood about how conceptually
`bounded information is extracted from the mix-
`tures of sounds that are typically present in inter-
`active settings. This is the problem of auditory
`scene analysis—how people make sense of what
`they hear. Just as people do, robots must be able
`to determine the location of sound sources and
`their type. They must associate certain sounds
`with the causes of the sounds and events. When
`interacting with people, robots must be able to
`converse on the basis of what they hear and see
`and may even have additional, nonspeech audito-
`ry display functions ranging from alerting to the
`playback of captured sounds. Social settings also
`raise practical performance issues for robots such
`as being interrupted while speaking, excessive
`ambient noise or quiet, the user’s physical listen-
`ing distance, the acceptability of being overheard
`or disturbing others, and so on.
`
`The purpose of this symposium is to gather to-
`gether researchers in machine listening, speech
`systems, and general robotics, as well as those in
`other disciplines, including AI, neuroscience, and
`the cognitive and social sciences, who are inter-
`ested in a collaborative, interdisciplinary explo-
`ration of the range of issues that concern aurally
`informed performance in robots. The goal is to
`share results, positions, and insights across
`boundaries that concern challenges in robotic au-
`dition, auditory presentation, and the integration
`of these functions with other sensory and pro-
`cessing systems in the context of human-robot
`interaction and the auditory needs and prefer-
`ences of users.
`
`Page 11 of 136
`
`

`

` Pattern and hypothesis sharing among tool
`sets (interlingua, work flows, etc.)
`
` Data and algorithm characterization
`
` Equality detection (alias resolution, etc.)
`
` Group detection (collaboration networks,
`etc.)
`
`Submissions
`Potential participants may submit a technical pa-
`per (up to 8 pages), or a short paper (up to 3
`pages) in the form of an extended abstract or a
`description of a proposed demo or poster. Poten-
`tial participants who are unable to submit a paper
`are encouraged to submit a one-page statement of
`interest. Submissions in PDF using AAAI format
`should be sent to murray@ai.sri.com.
`
`Organizing Committee
`Ken Murray (cochair), SRI International (mur-
`ray@ai.sri.com); Ian Harrison (cochair), SRI In-
`ternational (harrison@ai.sri.com); Fotis Barlos,
`BAE Systems; Tina Eliassi-Rad, Lawrence Liver-
`more National Laboratory; Henry Goldberg, Na-
`tional Association of Securities Dealers; Seth
`Greenblatt, 21st Century Technologies, Inc.;
`Dunja Mladenic, J. Stefan Institute; Robert Popp,
`Aptima, Inc.; Ben Rode, Cycorp
`
`Additional Information
`http://www.ai.sri.com/~murray/aaai-patterns/
`
`Pattern-based analysis of data plays an in-
`
`creasing role in several important applica-
`tions. In crime prevention (including secu-
`rities trading, tax fraud, and homeland security)
`it is being used both to detect evidence of crimi-
`nal events and to predict threatening activities be-
`fore they completely mature. In marketing it is
`being used to assess trends in the aggregate senti-
`ments of populations as well as the preferences of
`individuals. In epidemiology it is used to assess
`health trends in populations and provide early
`warning of epidemics. In these applications the
`data is typically incomplete and becomes avail-
`able incrementally over time, and it can often
`support alternative interpretations, so assessing
`the quality of the evolving evidence among a set
`of competing hypotheses is critical. This sympo-
`sium will bring together researchers from diverse
`backgrounds, including machine learning, data
`management, graph theory, link analysis, infor-
`mation retrieval, privacy, automated reasoning,
`and knowledge representation, to promote ad-
`vances in acquiring and using patterns for detect-
`ing and managing evidence in data.
`
`Topics
`Topics of particular interest include:
`
` Learning patterns from data
`
` Identifying patterns efficiently within mas-
`sive, structured, or partially structured data
`
` Matching algorithms for specific data charac-
`teristics (inexact matching, etc.)
`
` Reasoning with patterns (deduction, abduc-
`tion, induction, disjunction, negation, etc.)
`
` Representing patterns and hypotheses
`
` Hypothesis management (monitoring pre-
`dictions, interactive refinement, etc.)
`
` Managing conflicting and uncertain data
`(probabilities, knowledge gaps, etc.)
`
` Data and reasoning provenance
`
` Data access issues (privacy, secrecy, propri-
`etary, etc.)
`
` Applications (homeland security, fraud de-
`tection, epidemiology, marketing, etc.)
`
` Evaluation of pattern analysis systems
`
`for Evidence Detection
`Capturing and Using Patterns
`
`4 AAAI FALL SYMPOSIA
`
`Page 12 of 136
`
`

`

`Developmental Systems
`
` How can desirable design principles—such as
`adaptation, evolvability, scalability, and mod-
`ularity—be maximized in a developmental
`system?
`
` What kind of benchmarks and metrics could
`be used to test and compare different devel-
`opmental systems?
`
`The symposium schedule will be divided accord-
`ing to themes. Presentations will comprise peer-
`reviewed paper presentations and demonstra-
`tions of computer simulations. All presenters will
`be required to explain how their work fits into the
`area of computational development and explain
`its significance. Each session ends with an open
`discussion held amongst attendees debating is-
`sues brought out through the presentations.
`
`Submissions
`Those interested in participating in this sympo-
`sium should send either a full paper (8 pages
`maximum) or a position paper (1-2 pages) in
`AAAI format in PDF to Sanjeev Kumar at
`sk525@cornell.edu.
`
`Organizing Committee
`Sanjeev Kumar (cochair), Sibley School of Me-
`chanical and Aerospace Engineering, Cornell
`University (sk525@cornell.edu); Gregory S.
`Hornby (cochair), UCSC University Affiliated
`Research Center at NASA Ames Research Center
`(hornby@e-mail.arc.nasa.gov); Joshua Bongard
`(cochair), Sibley School of Mechanical and Aero-
`space Engineering, Cornell University (josh.bon-
`gard@cornell.edu)
`
`In nature, the processes of biological develop-
`
`ment have been pivotal in nature’s ability to
`construct adaptable, modularized, and self-
`repairing systems of incredible complexity. The
`development of multicellular organisms from a
`single cell provides a plentiful and rich source of
`knowledge and inspiration for constructing de-
`velopmental systems that model biological
`processes and/or enhance evolutionary design
`systems.
`
`Development biology-inspired approaches
`represent a method for facilitating the construc-
`tion of robust, complex adaptive systems in a
`more modular and evolvable manner than con-
`ventional methods. For example the state of the
`art in evolutionary robotics involves evolving
`controllers for robots with fixed morphologies,
`rather than all aspects of the robot. Artificial de-
`velopmental systems may be useful for overcom-
`ing this limitation: biological development relies
`on coupled growth of all of an organism’s sub-
`systems in parallel, and the evolution of modular
`gene sub-networks and phenotypic modules.
`
`This symposium is intended to stimulate dis-
`cussion about how best to extract the key princi-
`ples of biological development as they relate to
`design of complex artifacts and computation in
`general. We will focus discussions around the fol-
`lowing questions:
`
` Which mechanisms of biological develop-
`ment are useful as general design principles,
`and which are only relevant to biological de-
`velopment?
`
` What purpose does computational develop-
`ment serve?
`
` What is the current state of computational
`development and its future?
`
` What is the relationship between develop-
`ment and evolution in both natural and arti-
`ficial systems?
`
` How should we define the terms “develop-
`ment,” “morphogenesis,” and “regeneration”
`in our field, as opposed to how they are used
`in biology?
`
` How would one compare the design abilities
`of a standard evolutionary algorithm to a de-
`velopmental system?
`
`AAAI FALL SYMPOSIA 5
`
`Page 13 of 136
`
`

`

`Mental models formed by a robot to support
`rapid image comprehension: How does a robot
`formulate a mental model of an image that can be
`used to support rapid comprehension and deci-
`sion-making?
`
`Learning techniques for the enhancement of im-
`age comprehension capabilities: Over a period of
`time it is postulated that, with appropriate learn-
`ing mechanisms, the robot’s performance at im-
`age comprehension will improve. What are these
`mechanisms?
`
`Mathematical formulation of image comprehen-
`sion concepts: How can image comprehension be
`formalized to enable analysis and optimization?
`
`Submissions
`Those interested in participating in this sympo-
`sium should send either a full paper (8 pages
`maximum) or a position paper (1-2 pages) in
`AAAI format in PDF to walt.truszkowski@nasa
`.gov.
`
`Organizing Committee
`Walt Truszkowski (walt.truszkowski@nasa.gov),
`Jacqueline Le Moigne, Bir Bhanu
`
`Additional Information
`http://aaaisymposium.gsfc.nasa.gov/
`
`For most computer vision applications, a
`
`typical system is composed of the following
`four components: (1) acquisition—sensor
`inputs, (2) processing—object and pattern recog-
`nition and labeling, (3) analysis—means of ob-
`taining quantitative and qualitative information
`from an image, and (4) comprehension (under-
`standing)—knowledge about the image which
`supports rapid decision making and action.
`
`The underlying hypothesis of this symposium
`is that it may not be necessary to go through this
`sequence of steps in depth to arrive at some level
`of comprehension rich enough to support real-
`time decision-making and action.
`
`The symposium is interested in robotic image-
`comprehension (not image-acquisition, process-
`ing or analysis in the classical sense). We solicit
`papers that address the endowment of robots
`with a machine-intelligence approach to near re-
`al-time image comprehension. This may involve
`such things as novel representations and system-
`atic handling of evolving image information or
`the real- time generation and use of informal on-
`tologies to support the comprehension process
`from a semantic-technology perspective.
`
`Topics
`Topics of interest include the following:
`
`Rapid determination of the meaning of the con-
`tent of an image: In order to support near real-
`time decision-making on the part of a robot look-
`ing at the image of a scene, methods for assigning
`meaning to the images features are needed. What
`are they?
`
`Minimal clues (features) to support comprehen-
`sion: Assuming that for the rapid comprehension
`of an image by a robot only selected features in
`the image are necessary, then what are these fea-
`tures, how are these features selected, and how
`can a minimal number of features be identified?
`These are some of the questions that need to be
`addressed.
`
`Semantic (and syntactic) predisposition of a ro-
`bot to image comprehension: What does a robot
`need to know ahead of time in order to realize
`rapid image comprehension? What roles do lim-
`ited and unlimited ontologies play in image com-
`prehension? How does it obtain these ontological
`capabilities?
`
`Image Comprehension
`
`6 AAAI FALL SYMPOSIA
`
`Page 14 of 136
`
`

`

`Integrating Logical Reasoning
`into Everyday Applications
`
`AAAI FALL SYMPOSIA 7
`
`This symposium is concerned with all aspects of
`making logic accessible to everyday users, and in
`incorporating logical reasoners into everyday ap-
`plications. Such applications include, but are not
`limited to e-mail clients, spreadsheets, Web
`browsers, multimedia players, digital video
`recorders, digital calendars, digital address books,
`internet telephony applications, financial and ac-
`counting applications, and word processors.
`
`Organizing Committee
`Michael Kassoff (mkassoff@stanford.edu), Stan-
`ford University; Heiner Stuckenschmidt, Univer-
`sity of Mannheim; Andre Valente, Knowledge
`Systems Ventures; Michael Witbrock, Cycorp
`
`Additional Information
`http://logic.stanford.edu/everyday/
`
`Applications such as e-mail clients, Web
`
`browsers, spreadsheets and personal fi-
`nance programs have become an integral
`part of modern daily life. The user base of some
`of these programs are in the hundreds of millions
`of users.
`
`Logical reasoners can aid the users of these
`programs in several ways. Firstly, they can auto-
`mate routine, repetitive, or tedious tasks, freeing
`the user from doing so himself. Secondly, they
`can script time-critical actions to be taken by the
`application, even if the user is unavailable or not
`fast enough to do so himself. Finally, they can be
`used to constrain aspects of the program’s behav-
`ior to meet the user’s needs.
`
`For example, e-mail filtering rules save the user
`from having to send e-mail from a known spam-
`mer to the trash can and can take timely action
`such as automatically forwarding important e-
`mail to a coworker while the user is disconnected
`from the Internet. Or logical rules can specify
`constraints on what type of music an mp3 player
`should play during particular times of the day, or
`what types of programs a digital video recorder
`should record.
`
`Enhancing such applications with logical rea-
`soning brings the potential to spread the use of
`logic beyond the confines of specialized applica-
`tions and into the mainstream of computing.
`
`One application that has garnered attention re-
`cently is the logical spreadsheet. Logical spread-
`sheets have the potential of providing end users
`with automated support for making complex de-
`cisions based on symbolic reasoning in the same
`simple manner as current spreadsheets allow
`them to make complex decisions based on nu-
`merical data.
`
`Looking to the future, the promise of the se-
`mantic web has opened up the possibility of
`“scripting the world,” as logical rules can refer-
`ence arbitrary conditions on the Web and pro-
`duce corresponding side-effects on the Web. Fur-
`thermore, the semantic desktop movement
`promises to integrate ontologies and metadata in-
`to the everyday desktop environment.
`
`Page 15 of 136
`
`

`

` What are the knowledges, translations or
`other hierarchies that emerge in such set-
`tings?
`
` What tools do we use in these explorations?
`
` Are emergent phenomena surprising? if so, to
`whom? and what effects might such surprise
`register in a system composed of agents, phe-
`nomena and observer?
`
` Are they surprises to the agent?
`
` How do these phenomena reflect on the off
`and on-line societies?
`
`Submissions
`Those interested in participating in this sympo-
`sium should send either a full paper (10 pages
`maximum) or a position paper (1-2 pages) in
`AAAI format in PDF to Goran Trajkovski (gtra-
`jkovski@towson.edu).
`
`Organizing Committee
`Goran Trajkovski (cohair), Towson University
`(gtrajkovski@towson.edu); Samuel Collins (co-
`hair), Towson University; Georgi Stojanov,
`American University in Paris, France; Michael
`North, Argonne National Laboratories; Laszlo
`Gulyas, AITIA International Inc., Hungary
`
`Additional Information
`http://pages.towson.edu/gtrajkov/FSS2006/
`Welcome.html
`
`Whereas multiagent systems have been
`
`extremely helpful in solving engineer-
`ing problems, much of what we find
`exciting lies in their applications to contemporary
`human life. In particular, the focus of this meet-
`ing will be on self-constituting systems and net-
`works composed of human and nonhuman
`agents characteristic of emergent cyber cultures,
`including e-commerce, e-learning as well as other
`human/nonhuman agent systems in medicine,
`law, science and online interactions of all kinds. It
`represents an opportunity not only to share in-
`sights and experiments in multiagent systems
`composed of robot and software agents, but to
`theorize hybridity formed at the junction of the
`human and nonhuman. Multiagent systems, we
`submit, cross disciplinary boundaries by focusing
`on society and culture as emerging from the in-
`teractions of autonomous agents. Poised at the
`intersection of AI, cybernetics, sociology, semi-
`otics and anthropology, this strand of multiagent
`systems research enables a powerful perspective
`illuminating not only how we live and learn now,
`but also, through focusing on emergence, how we
`anticipate the future. Moreover, by convening this
`interdisciplinary symposium, we hope to form
`new network assemblages of variegated agents of
`researchers and their techniques out of which
`may arise new perspectives on heretofore
`parochial questions in our respective disciplines.
`From here, there are manifold policy implica-
`tions: multiagent systems research, we believe,
`can be a powerful reagent, interrogating the tele-
`ological, emergentist assumptions underlying, for
`example, the adoption and institutionalization of
`IT in universities, businesses, hospitals and
`NGOs, and suggesting other, networked possibil-
`ities.
`
`Key Questions
`Key questions include the following:
`
` Emergence of pre-linguistic concepts
`
` Emergence of shared representations
`
` Emergence of meaning and language
`
` How can we characterize the fungible, shift-
`ing networks created by human and nonhu-
`man agents?
`
` How do the environment and the society in-
`fluence the individual agent and vice versa?
`
`Phenomena in Societies of Agents
`Interaction and Emergent
`
`8 AAAI FALL SYMPOSIA
`
`Page 16 of 136
`
`

`

`Semantic Web for Collaborative
`Knowledge Acquisition
`
` Modeling, tracking and using information
`provenance
`
` Modeling and reasoning about trust of infor-
`mation sources and services
`
` Extracting knowledge and facts from distrib-
`uted text and multimedia data
`
` Preserving privacy, selective information and
`knowledge sharing
`
` Case studies, software tools, and prototypes
`
`The symposium will include a series of half-day
`sessions, each addressing a challenge area. Ses-
`sions will include invited talks providing
`overviews of key topics, short presentations based
`on contributed papers, a poster session for work
`in progress, breakout sessions focusing on specif-
`ic research challenges and emerging research di-
`rections, a panel discussion and a wrap-up ses-
`sion.
`
`Submissions
`Potential participants are invited to submit full
`papers (up to 8 pages in length), poster sum-
`maries or extended abstracts (1-2 pages in length)
`by May 1, 2006. Each submission will be reviewed
`by at least two program committee members. Au-
`thors of accepted papers and abstracts will be no-
`tified by May 22, 2006.
`
`Extended versions of selected papers may be pub-
`lished in a special issue of a journal or an edited
`book. Partial travel support for graduate and
`postdoctoral students may be available.
`
`Organizing Committee
`Vasant Honavar (chair), Iowa State University;
`Tim Finin (cohair), University of Maryland, Bal-
`timore County; Doina Caragea, Iowa State Uni-
`versity; Sally McClean, University of Ulster; Ion
`Muslea, Language Weaver, Inc; Raghu Ramakr-
`ishnan, University of Wisconsin-Madison; Steffen
`Staab, Koblenz University
`
`Recent advances in computing, communi-
`
`cations together with the rapid prolifera-
`tion of information sources and services
`present unprecedented opportunities in integra-
`tive and collaborative analysis and interpretation
`of distributed, autonomous (and hence, in-
`evitably semantically heterogeneous) data and
`knowledge sources and services in virtually every
`area of human activity. The symposium aims to
`bring together researchers in relevant areas of ar-
`tificial intelligence, databases, knowledge bases,
`machine learning, information integration, on-
`tologies, semantic web, web services, and relevant
`application areas (e.g., bioinformatics, environ-
`mental informatics, enterprise informatics e-sci-
`ence, e-government, medical informatics, securi-
`ty informatics, social informatics, among others.)
`to share recent advances in the state of the art in
`semantic web technologies for such applications.
`
`Topics
`Topics of interest include, but are not limited to:
`
` Cyber-infrastructure and semantic web tech-
`nologies for collaborative knowledge acquisi-
`tion
`
` Modeling semantically heterogeneous data
`sources and services
`
` Collaboratively developing and sharing of
`ontologies and inter-ontology mappings
`
` Discovering and resolving inconsistencies
`within and among ontologies
`
` Representing and reasoning with ontologies
`and mappings between ontologies
`
` Discovering mappings between data source
`schemas and between ontologies
`
` Querying distributed, semantically heteroge-
`neous information sources
`
` Acquiring knowledge from distributed, au-
`tonomous, semantically heterogeneous infor-
`mation sources
`
` Acquiring knowledge from part