1 KANAL: Knowledge ANALysis Jihie Kim Yolanda Gil USC/ISI

1

KANAL:Knowledge ANALysis

Jihie KimYolanda Gil

USC/ISI

www.isi.edu/expect/rkf/

2USC INFORMATION SCIENCES INSTITUTE KANAL

Role of Knowledge Analysis in SRI Team

To point out to the Interaction Manager what additional K needs to be acquired or what existing K needs to be modified

To guard the knowledge server from invalid statements entered by the user


Approach: Using Interdependency Models

Relating different pieces of Knowledge among themselves and to the existing KB(e.g., how different pieces of knowledge

are put together to generate an answer) Successfully used in checking

problem-solving K in EXPECT (Gil & Melz 96; Kim & Gil 99)


Current Focus: Checking Process Models

Verification checks: model is correct (e.g., no steps missing

Validation checks: model is as user intended (e.g., alert user of impossible paths)

UI Interaction Manager

KMKANAL

Interaction Plansfor fixing errors


Validating Complex Process Models

Enter

Arrive

Lambda Virus Invasion 2

Transcribe

Replicate

Circularize

Integrate Divide Disintegrate

Synthesize Copy

…

…Assemble

…

…


Describing Process Models (Composed Concepts)

Each individual step hasPreconditions, Add-list, Delete-list

Links among the steps Decomposition links between steps and

substeps Disjunctive alternatives Temporal links …

VirusInvasionsubsteps

EnterIntegrate

Synthesize

. . .disjunction


Checks on Process Models

All the steps are properly linked (substep, nextstep, disjunctive nextstep, conjunctive nextstep, …)

All the preconditions of each step are satisfied during the simulation

All the expected effects can be achieved There are no unexpected effects There are no impossible paths . . .


Current Focus: Dynamic Checks

Simulation (or symbolic execution) results show how substeps of the process model are related each other (Interdependency Model)

Perform various kinds of checks unachieved preconditions expected/unexpected effects disjunctive branches loops causal links redundancies unordered steps …

: Implemented


Checking Unachieved Preconditions During simulation, collect unachieved

preconditions by tracing failed expressions Suggest fixes

Add a step that can achieve the condition Add ordering constraints between the failed

step and another step that undid the condition Delete the step . . . VirusInvasion

Enter Integrate . . .

Failed Precondition: Virus near CellProposed Fixes: Add an Arrive step Add a Move step


Checking Effects

Compute the effects by simulation Suggest fixes for unachieved expected

effects Add steps that can achieve the effect Add ordering constraints between effect

adding steps and effect deleting steps

Check unexpected effectsAfter VirusInvasion ProteinCoat of the virus broken Achieved DNA of the virus has replicates Unachieved <Proposed Fixes>

Add a Replicate stepAdd a Divide step


CheckingDisjunctive Branches

Inform all the combinations of alternatives so that the user can check if some are impossible

KANAL can simulate and highlight disjunctive paths


Example: Lambda Virus Invasion

<Paths Simulated>

Path1: Arrive1 Enter2 Circularize3 Integrate4 Divide5 Disintegrate6 Synthesize7 Replicate8

Path2: Arrive1 Enter2 Circularize3 Synthesize7 Replicate8

(From Alberts ECB Chapter 9)

Enter Circularize


Synthesize Replicate

disjunctionArrive


Example:Conjunctive Branches

<Simulation sequence>

Arrive1 Enter2 Trascribe3 Replicate4 Assembly5Arrive1 Enter2 Replicate4 Trascribe3 Assembly5

Life cycle of a virus (from Alberts ECB Chapter 9)

Enter

Transcribe

Assemble

Replicate

ConjunctionArrive


Checking Loops

<Loops Found>

Loop1: Arrive1 Enter2 Circularize3 Integrate4 Divide5 Disintegrate6 Synthesize7 Replicate8 Arrive1

Loop2: Arrive1 Enter2 Circularize3 Synthesize7 Replicate8 Enter1Loop3: Divide5 Divide5

Enter Circularize



disjunctionArrive


Checking Causal Links

Describe which step enables (or disables)a given step

<Causal Links>

Arrive1 enables Enter2 by achieving “Virus near Cell” Integrate4 enables Disintegrate6 by achieving “Virus DNA integrated with chromosome”

Enter Circularize



disjunctionArrive


Fixing Problems: UsingInteraction Plans

Interaction Plan: describes how to proceed with the user interaction direct what to do next based on the results

from K Analysis KANAL’s dialogue for fixing errors is

implemented with interaction plans Will be integrated with the Interaction

Manager


Keeping Track of Interaction History

...Choose what to simulate choose model: VirusInvadesCell choose substep to test: VirusInvadesCellSimulate model VirusInvadesCell simulate-steps-&-find-failed-events ask-to-fix-failed-event: (failed preconditions of Enter) propose-fixes-for-failed-event ask-what-to-fix-for-failed-event : ((the location of (the patient of Enter)) = (the space-near of (the agent of Enter))) ask-how-to-fix-failed-event (add Arrive before Enter)


Future Extensions (I):Static Checks

Let user pose questions about various features of the process model to test the model

KANAL will maintain test suites Users pick from sample query templates

example: retrieving role values, part-of relations, type definitions,..

Users may specify their expected results Users may vary the initial situations to start from

Explanation or trace of the answer to a query show how different pieces of K are used to generate the answer (Interdependency Model)


Future Extensions (II)

Exploiting history and evolution of Interdependency Models (for both simulations and queries)Example: Check what tests were correctly answered

before Using heuristics to focus K analysis

Example: when invalid results are obtained, KANAL will use a divide-and-conquer strategy and check intermediate results to find the sources of the problem

Testing with different initial states and different arguments


Future Extensions (III)

Interdependency Models for problem solving knowledge EKCP Build on past work on EXPECT


Using KANAL for Intelligent Tutoring Systems ITSs can acquire domain knowledge from

human instructor and use simulations to refine the knowledge (Johnson et al 2000, Scholer et al 2000, Angros et al 99)

We are exploring the use of KANAL to check and analyze the domain models while it is being built


Knowledge Authoring Environment for Tutoring Systems (current)

Demonstration

Library of actions

DomainSimulator

Experimenter

Initial Model

RefinedModel

FinalModel

(Lessons)

Instructor

SteveAgent

Student


Knowledge Authoring Environment for Tutoring Systems (future)

EditorDemonstration

Library of actions

DomainSimulator

Experimenter KANAL

Initial Model

RefinedModel

FinalModel

(Lessons)

Instructor

SteveAgent

Student

1 KANAL: Knowledge ANALysis Jihie Kim Yolanda Gil USC/ISI

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