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Challenges for Building Mixed-Initiative Problem Solving Assistants John Lee - University of Iowa

Challenges for Building Mixed-Initiative Problem Solving Assistants John Lee - University of Iowa. Maintenance / Extensibility Standards / Interoperability Testing, Verification, Validation The empiricist view and the rationalist view.

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Challenges for Building Mixed-Initiative Problem Solving Assistants John Lee - University of Iowa

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  1. Challenges for Building Mixed-Initiative Problem Solving AssistantsJohn Lee - University of Iowa • Maintenance / Extensibility • Standards / Interoperability • Testing, Verification, Validation • The empiricist view and the rationalist view

  2. Challenges for Building Mixed-Initiative Problem Solving AssistantsJohn Lee - University of Iowa • Maintenance / Extensibility • Expansion to new paradigms… • Uncertainty • Time, Space, Events, Causality, Possession • Feedback / Learning / Improvement • User Modeling • Fault-Tolerance • Emotional Modeling

  3. Challenges for Building Mixed-Initiative Problem Solving AssistantsJohn Lee - University of Iowa • Standards / Interoperability • Domain independence • Application independence • Component reusability

  4. Challenges for Building Mixed-Initiative Problem Solving AssistantsJohn Lee - University of Iowa • Testing, Verification, Validation: • Observance of functionality • Absence of unwanted behavior • What are Design Requirements and what are Behavior Specifications?

  5. Scientific Views* • Rationalist View • Quest for Certainty and Completeness • Thought (Reasoning and Deduction) • Focus on Logical and Mathematical Models • Empiricist View • Uses what is known to develop knowledge • Generalizes based on partial knowledge * Peter Wegner. “Why Interaction is More Powerful Than Algorithms.” CACM-40-5, 1997

  6. Complexity of Human Interaction • Rationalist View • Create a specific protocol which will be complete and well-formed. • Force the human to use this protocol when interacting with an agent. • Bring the human from uncertainty to certainty by only accepting certain inputs in certain states. • Menu-driven selection

  7. Complexity of Human Interaction • Empiricist View • Use knowledge of human-human interaction to attempt to create specific behaviors. • Incorporate these behaviors into a protocol. • Allow the protocol to be incomplete. • Thus bringing the agent from certainty to uncertainty to avoid inhibiting the human’s expressiveness.

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