David W. AhaNavy Center for Applied Research in AI

Naval Research Laboratory

Co-chairs

Gheorghe TecuciLearning Agents Center

George Mason University

Previous Workshops on Mixed-Initiative

AAAI'99 Workshop on Mixed-Initiative Intelligence

ECCBR'02 Workshop on Mixed-Initiative CBR

ICCBR'03 Workshop on Mixed-Initiative CBR

IJCAI'03 Workshop on Mixed-Initiative Intelligent Systems

ICAPS'05 Workshop on Mixed-Initiative Planning and Scheduling

Math and Photos

32 Participants26 Papers

1 Panel Discussion

What Are They?

Mixed-Initiative Interaction

Problem Solving Assistant

Eric Horvitz

“I shall use the phrase to refer broadly to methods that explicitly support an

efficient, natural interleaving of contributions by users and automated

services aimed at converging on solutions to problems”.

• Has Expert Knowledge in a Domain

• Helps the user in solving problems

© 2000 David Deckert Competence

Inte

ract

ion

stupid intelligent

lazy

active

What is needed

Mixed InitiativeProblem Solving Assistant

IntelligentUser Interfaces

Learning

DiscourseTheory

ProblemSolving

KnowledgeRepresentation

Multi-AgentSystems

communicate

interactinteract

observe observe

plan tree

focus stack

COLLAGEN

discourse model

beliefs

intentions

desiresfirst-principles planning

discourse interpretation

plan recognition

problem solving model

COLLAGEN (Rich, Sidner, et al.)

Dialogue-based Systems (Ferguson & Allen)

BeliefsDesiresIntentions

BeliefsDesiresIntentions What to do?What to do?

ExecuteExecuteObserveObserve

BDI Agent

ISY-travel(Viappiani, Faltings et al. )

Minerva & Genoma(Wilkins & Fried)

GE Call Center for Diagnosis(Cheetham)

CMRadar(Modi et al.)

CALODisciple

(Tecuci, Boicu et al.)

• Task model

• Belief model

• Plan recognition

• Multi-agent multi-human interaction

• When to show initiative

• User awareness

• Evaluation methodology

Challenges