AAAI Fall Symposium on Mixed-Initiative Problem-Solving Assistants 1 Mixed-Initiative Dialogue Systems for Collaborative Problem-Solving George Ferguson

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AAAI Fall Symposium on Mixed-Initiative Problem-Solving Assistants

Mixed-Initiative Dialogue Systems for Collaborative Problem-Solving

George Ferguson & James AllenUniversity of Rochester

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Motivation

Eric Horvitz on “mixed-initiative” (2000): 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.

Natural language dialogue systems for mixed-initiative problem solving

Efficient: easy to say complicated things Natural: no training Emphasizes role of the user

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Goals Describe an architecture for mixed-initiative

dialogue systems such that: The system is able to do many things (in parallel)

e.g., search the web, plan activities, learn new tasks, observe its environment, ...

Dialogue-based interaction with a user is one of those things (albeit an important one)

Dialogue is in service of collaboration--we talk together in order to work together to solve problems

Collaboration is driven by principles of collaborative activity (joint intention)

Initiative (and mixed-initiative interaction) arises naturally from agents managing their joint intentions

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Outline Architecture of Mixed-Initiative Dialogue Systems

Dialogue Systems Agents Collaborative Agents

Components of Collaboration Ontology of collaborative problem solving acts User- and system-initiative APIs

Extended Example User initiative

Interpretation System initiative

Collaborative behavior Proposals Agreement

Other Issues

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Other Issues

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Dialogue Systems:The Standard Approach

A standard dialogue system is not an agent

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BDI Agents (briefly)

BeliefsDesiresIntentions What to do?

ExecuteObserve

Goal AssessmentGoal PrioritizationUtility Assessment...Hand-coded ProceduresReactive ControlLearned PolicyAdaptive PolicyMeans-Ends PlanningInteractive Control...

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Architecture of a Collaborative Dialogue Agent

Overall behavior controlled by Task Manager

Dialogue behavior under Dialogue Manager’s control

Dialogue Manager components operate independently and asynchronously

All components use shared BDI knowledge base (KB)

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Other Issues

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Collaboration Manager Ontology of

collaborative problem solving acts

User initiative: intentions from CM to TM

System initiative: intentions from TM to CM

CPS Act Ontology

System Initiative APIUser Initiative API

Collaboration Manager

Task Manager

Interpretation Generation

JointIntentions

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Collaborative Problem Solving Act Ontology

Ontology of collaborative acts that an agent can perform

Propose, Accept, Reject, Report, Check, Ask

Modality-independent Uses BDI language for

content Bel, Des, Commit “Know-ref” or “Know what

is” forms e.g. “Let’s buy a book”

(Propose USR SYS (Commit (USR SYS) (Do PURCHASE123)))where PURCHASE123 has object = BOOK456, ...

System Initiative APIUser Initiative API


Task Manager


JointIntentions

CPS Act Ontology

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System Initiative API

User Initiative API User utterances interpreted

using BDI state and principles of collaborative activity

Under the right conditions, user initiative results in suggestion that the Task Manager adopt a joint intention

Decision to adopt is up to the agent (Task Manager), not the dialogue subsystem

Asynchronous accept/reject from TM drives dialogue

If accepted, new intention drives agent behavior

CPS Act Ontology


Task Manager


JointIntentions

User Initiative API

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User Initiative API

System Initiative API Arises from Task

Manager assigning a collaborative goal (joint intention) to Collaboration Manager

CM determines dialogue behavior based on BDI state and principles of collaborative activity

TM asynchronously informed of success or failure

CPS Act Ontology


Task Manager


JointIntentions

System Initiative API

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Other Issues

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Example DialogueUSER: I need to purchase an LCD projector for my class.

I need XGA resolution and it has to be portable.Find an appropriate machine and get approval to purchase it by this afternoon.

SYSTEM: Ok. What is the budget?USER: 700 dollars.SYSTEM: Ok....SYSTEM: I’ve found three projectors that match your specifications.

[displays table]USER: Let’s go with the Hitachi....SYSTEM: There’s a problem with the projector purchase. It’s 4 p.m. and I

haven’t yet received approval from Fred.USER: You don’t need to get approval if the cost is less than 1000 dollars.SYSTEM: Ok.

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Other Issues

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User Initiative (1)

USER: I need to purchase an LCD projector for my class.

Direct report of a want or need:

(Report USR SYS(Des USR (Done PURCHASE123)))

Response: “Thanks for letting me know.”

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User Initiative (2)


Statement of a goal being pursued independently:

(Report USR SYS(Commit USR (Done PURCHASE123)))

Response: “Good luck with that.”

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User Initiative (3)


Proposal that a joint commitment (goal) be adopted:

(Propose USR SYS(Commit (USR SYS)

(Done PURCHASE123)))

If adopted, drives collaborative behavior

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Supporting Interpretation Not the focus of this paper but...

Crucial for natural language Also crucial for understanding actions of other

agents Need to interpret others’ actions/utterances

consistently with one’s beliefs and principles of collaborative activity

We use the same procedures that drive the agent’s collaborative behavior in reverse to help interpret the user’s utterances

Effectively, interpret it as a given CPS act if we might have performed that act given the current BDI state

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User Initiative API User proposals handled as

suggestions that the system adopt a joint commitment:

(suggest (Commit (USR SYS) (Done PURCHASE123))

If accepted: “Ok.” And new commitment

drives subsequent behavior

If rejected: “No. ...”

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Reasoning Requirements for User Initiative Have to be able to decide whether to adopt new

commitments Have to to be able to do this for oneself anyway Some strategies for committing to goals:

Hardcode goals that are acceptable If I know a way of achieving the goal (by myself or

collaboratively), then adopt it If achieving the goal is not incompatible with my beliefs,

desires, and intentions, then adopt it Can take initiative to gather information necessary

for decision Response to dialogue sub-system is asynchronous See next section...

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Other Issues

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System Initiative

Knowing when collaboration is necessary Collaborative dialogue behavior Proposals Agreement

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Knowing When Collaboration Is Necessary Task Manager needs to know what aspects of

a task require joint commitment Hard-coded into task models Compiled into procedures by combining task

models with general principles of collaboration Incremental meta-decision of execution system ...

For our example, assume it knows that we need to agree on the budget for purchasing the projector

Perhaps other aspects it can decide on its own Perhaps have to agree on what aspects need to be

agreed!

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System Initiative API Task Manager dispatches

collaborative goal to Collaboration Manager:

(Commit-What-Is (USR SYS)(the budget of PURCHASE123))

Collaborative goals drive dialogue behavior

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Collaborative Dialogue Behavior Collaboration Manager is an agent that

achieves its collaborative goals by performing CPS acts (leading to dialogue behavior)

Reactive procedures use BDI state to select CPS acts

These rules are compiled versions of the axioms defining the CPS acts ala Cohen & Levesque

For our example, it decides to:(RFP SYS USR (the budget of PURCHASE123)))

Generation produces:“What is the budget?”

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Proposals

Suppose the user answers:“700 dollars”

Context leads to interpretation as proposal:

(Propose USR SYS (Commit-What-Is (USR SYS) (the budget of PURCHASE123) (* 700 dollars)))

Handled uniformly as suggestion that Task Manager adopt the commitment

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Agreement

Generation produces: “OK” Collaboration Manager execution will now

realize that the goal of reaching agreement on a value for the budget has been achieved

Reports successful completion of the goal to the Task Manager

Shared BDI KB contains the new knowledge about the budget

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Other Issues

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Some Other Issues (1)

Is this only about natural language? No. But need an interface where:

Content is explicitly represented Actions are represented as CPS acts

Seems like A Good Thing in any event

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Some Other Issues (2)

Isn’t there more to collaboration than dialogue? Yes. But dialogue is useful enough (and hard

enough) to be worth focusing on Our approach embeds dialogue in a

general theory of collaborative activity

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Conclusions An architecture for mixed-initiative problem

solving assistants Particular emphasis on dialogue systems

True mixed-initiative system Goals and commitments come from either party

The system’s collaborative behavior is driven by a formal model of collaborative activity

Which also supports interpretation of user’s behavior

Completely domain- and application-independent

But very knowledge-intensive

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Conclusions

A practical way to build collaborative dialogue systems in many domains

Logistics planning Personal health care Command and control Agent team coordination Office assistant NL transcription and knowledge mining Crisis management ...

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For More Information...

George [email protected]

James [email protected]

http://www.cs.rochester.edu/~ferguson/http://www.cs.rochester.edu/research/cisd/

Documents

AAAI Fall Symposium on Mixed-Initiative Problem-Solving Assistants 1 Mixed-Initiative Dialogue Systems for Collaborative Problem-Solving George Ferguson