computational modeling of cognitive processes in plan ... · computational modeling of cognitive...

Computational Modeling of Cognitive Processes in Plan Authoring

J. William Murdock & David W. AhaIntelligent Decision Aids Group

Navy Center for Applied Research in Artificial IntelligenceNaval Research Laboratory, Code 5515

Washington, DC 20375{murdock,aha}@aic.nrl.navy.mil

http://www.aic.nrl.navy.mil/~aha/ida/

TC3 Workshop: Cognitive Elements Of Effective Collaboration(January 15-17 2002, San Diego)

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Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18

Murdock & Aha, NRL 2/16

Context

Task: Plan authoring• Intelligent system collaborates with human user• Human is in charge; system makes recommendations

Task: Plan authoring• Intelligent system collaborates with human user• Human is in charge; system makes recommendations

Key Assumption:• Human has a better “big picture” understanding of the

situation than does the intelligent system

Key Assumption:• Human has a better “big picture” understanding of the

situation than does the intelligent system

Benefit:• When the system makes a good recommendation, the

user can accept rather than having to manually enter a new step in the plan.

• Faster plan authoring

Benefit:• When the system makes a good recommendation, the

user can accept rather than having to manually enter a new step in the plan.

• Faster plan authoring


Challenge

• An intelligent system can recommend actions for a plan based on its limited knowledge.

• We are considering situations in which the human has a better general understanding of the problem.

• The recommendation the system makes will, at first, be worse than what the human can do.

• How can we get the system to improve during the course of the planning process?

• An intelligent system can recommend actions for a plan based on its limited knowledge.

• We are considering situations in which the human has a better general understanding of the problem.

• The recommendation the system makes will, at first, be worse than what the human can do.

• How can we get the system to improve during the course of the planning process?


Our Main Theme

1. Determine:a. Goals: what the user is trying to dob. Approach: how the user is trying to do it

2. Generate suggestions that are compatible with both – i.e., Because the user is the expert, understand the user

and then do things the user’s way.

1. Determine:a. Goals: what the user is trying to dob. Approach: how the user is trying to do it

2. Generate suggestions that are compatible with both – i.e., Because the user is the expert, understand the user

and then do things the user’s way.

System requirement: A cognitive model of the userSystem requirement: A cognitive model of the user

Goal: Travel from NRL to USD


Cognitive Models

Task-Method-Knowledge (TMK):– Tasks: What a part of a process does.– Methods: How a part of a process works.– Knowledge: What the process uses and alters.

Task-Method-Knowledge (TMK):– Tasks: What a part of a process does.– Methods: How a part of a process works.– Knowledge: What the process uses and alters.

by Car by Train

…

Maps, Routes,Vehicles, etc. Travel

Start Car Drive Stop Car

Existing work on TMK has involved:– Intelligent systems that automatically adapt– Executable cognitive models of recorded protocols– Many other topics– But never cognitive models of users

Existing work on TMK has involved:– Intelligent systems that automatically adapt– Executable cognitive models of recorded protocols– Many other topics– But never cognitive models of users


TMK AnalysisInterpret the user’s reasoning and goals

TMK AnalysisInterpret the user’s reasoning and goals

Overview of Decision Making Architecture

TMK PredictionInfer what the user intends to do next

TMK PredictionInfer what the user intends to do next

Automated PlanningSelect actions that accomplish the goals

Automated PlanningSelect actions that accomplish the goals

Recommendation FilteringEliminate actions that are inconsistent with

the predictions of a user’s intentions

Recommendation FilteringEliminate actions that are inconsistent with

the predictions of a user’s intentions


User

Plan Authoring Tool

Recommendation

RecommendationFiltering

ExpectedBehavior

TMK Prediction

Knowledge Task

Method Method Method

Task

Task Task Task …

TMK Cognitive Model of the User

Interpretationof user’s

reasoning

Inferred Goal

TMKAnalysis

Action …Action

Fact Operator

Fact Operator…

Potential Actions

Automated Planner


An Illustrative Logistics Example

• User has some boxes to ship and two available trucks.• One truck is faster, so a planner will recommend it.• The user wants to use the slower truck.• Challenge: Recognize that the user has chosen the

slower truck and make recommendations that abide by that choice.

• User has some boxes to ship and two available trucks.• One truck is faster, so a planner will recommend it.• The user wants to use the slower truck.• Challenge: Recognize that the user has chosen the

slower truck and make recommendations that abide by that choice.


Slow Truck

Boxes

Slow Truck

What the user wants

Slow Truck

Fast Truck

Slow Truck Slow Truck Slow Truck Slow TruckSlow TruckSlow Truck

Boxes


What the automatedplanner would do

Slow Truck

Fast Truck Fast Truck Fast Truck Fast TruckFast Truck

Boxes

Fast TruckFast Truck Fast Truck

Boxes

Fast Truck


Recommendations withoutcognitive modeling

Slow Truck

Fast Truck

Slow TruckSlow Truck

Boxes

Slow Truck

Boxes

Slow Truck Slow Truck Slow Truck Slow Truck Slow Truck


Recommendations withcognitive modeling

Slow Truck

Fast Truck

Slow TruckSlow Truck

Boxes

Slow Truck

Boxes

Slow Truck Slow TruckSlow Truck Slow Truck Slow Truck


Plan Authoring Tool

TMK Prediction

Input DriveAction

User

RecommendationFiltering

Drive(SlowTruck)

Load(Box1,SlowTruck)

…Load(Box2,SlowTruck)

TMK Cognitive Model of the User

ConstructShipping Plan

LinearDeliberation …

Decide onVehicle … Input Load

Action

…

Interpretation:Decided on SlowTruck

Goal: Move boxes

TMKAnalysis

Input DriveAction

Trucks,Boxes,

Locations

Unload(Box1,SlowTruck)

Drive(SlowTruck)

Boxes Unload

Trucks Drive…

Automated Planner


Domain Applicability

• Data-intensive environments– System can make a significant contribution

• Decisions require additional background knowledge and/or subjective judgments– System must collaborate with the user

• Expert human users– System’s approach should match user’s preference

• Data-intensive environments– System can make a significant contribution

• Decisions require additional background knowledge and/or subjective judgments– System must collaborate with the user

• Expert human users– System’s approach should match user’s preference

• Example: Noncombatant Evacuation Operations (NEOs)– Tasks: Deliberative and execution-time planning– Data: Doctrine, SOPs, and records of past NEOs are available– Requires that human have final authority over decisions

• Example: Noncombatant Evacuation Operations (NEOs)– Tasks: Deliberative and execution-time planning– Data: Doctrine, SOPs, and records of past NEOs are available– Requires that human have final authority over decisions


Open Issues

• Is TMK adequate for modeling users?– If not, what augmentations are needed?

• Where do TMK user models come from?1. Encoded by system designers from cognitive studies?2. Extracted automatically through experience?3. A combination of (1) and (2)?

• Is information from user actions adequate for judging user intentions?

– If not, what other information can enable coordination between the user and the system?

• Is TMK adequate for modeling users?– If not, what augmentations are needed?

• Where do TMK user models come from?1. Encoded by system designers from cognitive studies?2. Extracted automatically through experience?3. A combination of (1) and (2)?

• Is information from user actions adequate for judging user intentions?

– If not, what other information can enable coordination between the user and the system?


Summary

• Intelligent system collaborates with a human user; the system provides recommendations during plan authoring.

• Cognitive model is used to infer what the user wants to do and how the user wants to do it.

• User’s cognitive model is composed of Tasks, Methods, and Knowledge (TMK)

• Proposed tool recommends actions for doing what the user wants in the way that the user wants to do it.

• Intelligent system collaborates with a human user; the system provides recommendations during plan authoring.

• Cognitive model is used to infer what the user wants to do and how the user wants to do it.

• User’s cognitive model is composed of Tasks, Methods, and Knowledge (TMK)

• Proposed tool recommends actions for doing what the user wants in the way that the user wants to do it.

computational modeling of cognitive processes in plan ... · computational modeling of cognitive...

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