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Ambient Computational Environments

Ambient Computational Environments. Sprint Research Symposium March 8-9, 2000 Professor Gary J. Minden The University of Kansas. Electrical Engineering and Computer Science. This is a Road-Donkey. Carries all computer and communications devices with him

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Ambient Computational Environments

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  1. AmbientComputationalEnvironments Sprint Research Symposium March 8-9, 2000 Professor Gary J. Minden The University of Kansas Electrical Engineering and Computer Science

  2. This is a Road-Donkey • Carries all computer and communications devices with him • Deals with multiple network connections (is it a Hotel-9 or Hotel-8?) • Mentally reconciles multiple versions of tomorrow’s presentation • Spends more time making the computer/communication complex work, than working

  3. This is an ACE • Computationalresources built-in • Authenticated and authorized access • Individual portals to computational workspaces • Use and command local resources

  4. Ambient Computational Environments • Long-lived, widely accessible workspaces • Computational resources are available throughout the environment via access ports • Users co-opt local resources • Secure and private • Multi-modal interaction • Speech, gesture, tactile

  5. ACE Technology Interaction Language Systems Agents Network Services • Robust, available, persistent state • Location independent processing, dynamic network services, agent services • Individual and environmental access

  6. ACE — Research Challenges • Programming Environments • Programming Languages • Cooperative Task Negotiation • Contextual Information Retrival • Disambiguation • Networking Architecture

  7. ACE — Programming Environments • What is the division of functionality between a Personal Interaction Device (PID) and the ACE? • How is context named/identified within the ACE? • How does one use the PID to manipulate a potentially significantly larger surrounding environment? • In a shared context with other owners/PIDs, how does one negotiate for screen space and objects? • How do we build a user interface for PIDs that is comfortable with minimal training? • How do we manage the potentially large number of active computations, resources, and environments with a modestly sized interface?

  8. ACE — Programming Languages • What programming language abstractions are useful and necessary in an ACE? • How do you determine your location within the ACE? • How do you find and connect to other programming contexts? • How do you name, index, and search for resources within an ACE? • If we allow persistent Contexts, how do we update such Contexts over time? • If we wish to upgrade part of the physical infrastructure, how do we "tell customers to leave the facility" and "close the door"? • How do we account for system usages?

  9. ACE — Cooperative Task Negotiation • How does one define collaboration workspaces? • What functions are necessary for combining individual workspaces into collaborative workspaces? • How do individuals establish independent views of shareable workspaces and environments? • How do PIDs represent and communicate workspaces and negotiate? • What are negotiable resources? • How do Workspaces and Contexts describe themselves to be recognizable? • How can I interrupt the execution of any program, pick up the intermediate state, and move it somewhere else to run?

  10. ACE — Contextual Information Retrival • Support a wide range of search criteria, including timeliness, information quality, media, computational resources available. and location and time • Infer the appropriate search criteria from the user's workspace • Integrate multiple documentation formats for search and retrieval

  11. ACE — Disambiguation • Resolution in Spoken Natural Language Understanding • Resolution in Context of Robot Vision • Resolution with Machine Learning • Resolution in Deductive Reasoning and Planning • Resolution with Memory Systems • Resolution in Tactile Sensing and in Robotic Actuation

  12. ACE — Network Architecture Application API API API OS Network Display Application Keyboard OS ACE — Applications linked through Network connedtions Today’s approach

  13. ACE — Vision • Pervasive Embedded Resources • In buildings, people, vehicles • Interconnected with dynamic network services • Multiple, rich resource types - displays, computations, communications, information management, ... • Long-lived, widely accessible workspaces • Maintain distributed, available, consistent state • Multiple location and information services • Secure and private • Active connections based on current context • Disassociate process/task execution from physical location and network address • Enables mobile and replicated tasks • Implement tasks as services with multiple access mechanisms, e.g. network, video, sensor, actuator

  14. ACE — Key Technologies • Human/Computer Interaction • New techniques, new devices, new mobile communications • Programming Languages and Systems • High level abstractions, mobile and persistent tasks, long-lived workspaces • Resource recognition, task negotiation, co-opt local resources • Contextual Information Management • Disambiguation in multi-modal interaction

  15. ACE Personnel • G. Minden (PI) • A. Ambler (HCI, Programming languages and systems) • F. Brown (AI systems) • J. Evans (Networking and Computing Systems) • C. Tsatsoulis (Expert Systems, agent systems, and case based reasoning) • A. Agah (Robotic Systems) • S. Gauch (Information Retrieval) • D. Niehaus (Distributed Systems and Real-time) • J. Miller (Graphics) • J. Gauch (Video Information Systems) • J. Grzymala-Busse (Learning Systems) • T. Schreiber (Human Information Retrieval) • S. Speer (Psycholinguistics) • W. P. Alexander (System design) • J. James (Distributed Systems)

  16. Ambient Computational Environments Information and Telecommunications Technology Center Electrical Engineering andComputer Science

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