Transcript Dagstuhl (Agents, SAB)

13th Japan-Germany Forum on Information Technology
Virtual Sales Agent for
Personalized Internet Shopping
Wolfgang Wahlster
German Research Center for Artificial
Intelligence, DFKI GmbH
Stuhlsatzenhausweg 3
66123 Saarbruecken, Germany
phone: (+49 681) 302-5252/4162
fax: (+49 681) 302-5341
e-mail: [email protected]
WWW:http://www.dfki.de/~wahlster
Three Generations of Web Sites
First Generation
Second Generation
Interactive Web
Sites
Static Web Sites
Fossils cast in HTML
Third Generation
Virtual Webpages
JavaScripts and Applets
Netbots,
Information Extraction,
Presentation Planners
Database Access and
Template-based Generation
User Modeling,
Machine Learning,
Online Layout
Dynamic Web Sites
Adaptive Web Sites
© W. Wahlster, DFKI
What are
Virtual Sales
Agents?
l appear as life-like characters
l plan interactive behavior
autonomously
l can initiate interaction
ACTIVE
l understand the user‘s
requests
l answer clarification
questions
l allow mixed initiative
dialogs
REINTER- INTERFACE
ACTIVE AGENTS ACTIVE
l respond immediately
to interruptions
l criticism and
clarification questions
l direct manipulation
PROACTIVE
l anticipate the user's needs
l adopt the user's goals
l provide unsolicited comments
© W. Wahlster, DFKI
The Idea of Personalized Netbots
e.g. MetaCrawler
Softbots
Personal
Assistants
Indices,
Directories,
Search Engines
Mass
Services
WWW
Traveller’s Netbot: Tries to achieve traveller’s goals (finding and executing plans)
l
l
l
l
checks availability
finds best price
uses personal preferences (e.g. frequent flyer programme, seating preferences)
lets the traveller know, when seats become available (active help)
© W. Wahlster, DFKI
Intelligent Web Services
Consumer
buys
l Information
l Goods
l Services
Web Sites
Netbot
l Intelligent Parallel Retrieval
l Information Extraction and
Summarization
l Personalized Presentation
l Matchmaking
l Teleshopping Assistance
l Telemarketing Assistance
l Translation Services
l Data Mining Services
Provider
sells
l Information
l Goods
l Services
Knowledge about:
l Usage Patterns
l User Models
l Consumer Profiles
© W. Wahlster, DFKI
Intelligent Agent Technology is a Prerequisite
for Advanced WebCommerce
Virtual Web
Pages
Shopbots for
Automated
Comparison
Shopping
Text Analysis
and Generation
Multimedia
Presentation
Planning
Information Extraction from
HTML/XML Documents
Advanced
WebCommerce
User Modeling and Language Generation
Coordinated Text & Graphics Planning
Machine
Translation
Intuitive,
Multilingual
Access
Multimodal
Interfaces
Robust Dialogue
Understanding
Advanced Speech
Synthesis
One-to-One
Marketing
Dialogue with
Virtual Sales
Agents
© W. Wahlster, DFKI
Virtual Market Places with Human and
Machine Agents
© W. Wahlster, DFKI
Five Generations of Internet Applications
2000
Embedded
Internet Agents
Mobile
Internet
Services
WWW
Research Net
1
EMail
2
3
4
5
Every Car has
Internet Access
a homepage,
via WAP and UMTS
Agents are main
devices
Internet users,
Ubiquitious Computing
t
© W. Wahlster, DFKI
Towards Mobile and Speech-based
E-Commerce Using WAP Phones
l WAP phones
(Wireless Application
Protocol for Cellular
Phones)
l WML as a markup
language for interactive
content
l Mobile access to virtual shops allows price comparisons during real shopping
l Multimodal dialog: Voice In (Speech) - Web Out (Graphics, Hypertext)
l Voice input using advanced speech understanding technology
l Easy to use: customers simply say what they want
© W. Wahlster, DFKI
What is a Virtual Web Page?
Virtual Memory, Virtual Relation, Virtual Reality...
A Virtual Web Page
l is generated on the fly as a combination of various media objects from
multiple web sites or as a transformation of a real web page.
l looks like a real web page, but is not persistently stored.
l integrates generated and retrieved material in a coordinated way.
l can be tailored to a particular user profile and adapted to a particular
interaction context.
l has an underlying representation of the presentation context so that
an Interface Agent can comment, point to and explain its components.
© W. Wahlster, DFKI
Virtual Webpage Retrieved from 5 Different Servers
© W. Wahlster, DFKI
AiA: Information Integration for Virtual Webpages
PAN Travel Agent Andi
Car Route Planner
Yahoo
News
Server
Yahoo
Weather
Server
Hotel
Guide
Gault Millau
Restaurant
Guide
© W. Wahlster, DFKI
The Generation of Virtual Webpages with PAN and AiA
Hotel
Agent
Trip Data
Address
Netbot
PAN
Map
Agent
AiA
Pictures and
Graphics
Presentation
Planner
Pieces of Text
Components
of virtual
Webpages
Coordinates for
Pointing Gestures
Input for Speech
Synthesis
Icons for
Hyperlinks
Virtual
Web
Presentation
Persona
Server
Constraintbased
Online
Layout
Weather
Agent
Train & Flight
Scheduling
Agent
Major Event
Agent
© W. Wahlster, DFKI
Persona as a Personal Travel Consultant
© W. Wahlster, DFKI
A Natural Language Agent for Finding Pre-Owned
Porsche Cars
Boxter, not red, must
have AC, less than 20k
© W. Wahlster, DFKI
Enhanced ECommerce through Personalization
System is able to flexibly tailor
product presentations to the
individual user and the current
situation.
An animated character
serves as “Alter Ego”
of the presentation system.
Personalized Presenters at DFKI
© W. Wahlster, DFKI
PPP’s Persona Server implements a generic Presentation Agent
that can be easily adapted to various applications
Visual Appearances
Behaviors
l
l
l
l
Hand-drawn
Cartoon
Bitmaps
Presentation Gestures
Reactive Behaviors
Idle-time actions
Navigation actions
Persona
Server
Auditory Characteristics
l Sound effects, auditory icons
l Voice: male, female
Video Bitmaps
Generated
Bitmaps
from
3D-Models
© W. Wahlster, DFKI
Classification of Persona Gestures
Gesture Catalogue
Talking Posture 1
• cautious, hesitant
• appeal for compliance
• avoids body-gestures
Talking Posture 2
• active, attentive
• self-confident
• uses body-gestures
© W. Wahlster, DFKI
Context-Sensitive Decomposition of Persona Actions
High-Level
Persona Actions
Context-Sensitive
Expansion
take-position (t1 t2)
point-to (t 3 t 4)
move-to (t1 t2)
r-stick-pointing (t 3 t4)
(including Navigation Actions)
Decomposition
into
Uninterruptable
Basic Postures
r-turn (t 1 t21)
r-hand-lift (t3 t 31)
r-step (t 21 t22)
f-turn (t22 t2)
r-stick-expose (t 31 t 4)
Bitmaps
...
...
...
...
© W. Wahlster, DFKI
Extensions of the Representation Formalism
Distinction between production and presentation acts
(i.e. Persona- or display acts)
Explicit representation of qualitative and quantitative constraints
Production Act
Presentation Act
Introduce
CreateGraphics
S-Show
S-Position
Elaborate-Parts
S-Wait
Label
Label
S-CreateWindow
S-Depict
S-Point
S-Speak
S-Point S-Speak
Qualitative constraints: Create-Graphics meets S-Show, ...
Metric constraints: 1 <= Duration S-Wait <= 1, ...
© W. Wahlster, DFKI
PET: Persona-Enabling Toolkit
Objective:
l Enable non-professional computer users to populate their
web pages with lifelike characters
PET comes with:
l a set of characters and basic gestures
l an easy-to-learn Persona markup language
Developer’s PET will include:
l a character design tool which enables users to build their
own characters
Technical Realization:
l Based on XML and Java
© W. Wahlster, DFKI
The Persona Markup Language
Specification of
Persona actions
<html>
<head>
Specification of the
<title> Persona Test </title>
character to be used
</head>
<body>
<persona bitmap=“cartoon” ...>
<uselib url= .../>
<do name=“greet”/>
<do name =“speak” args=“hello”/>
</persona>
</body>
</html>
Features:
– XML-based
– easy to learn
© W. Wahlster, DFKI
Functional View of PET
Bitmaps
Webpage with Reference to
Java Applet
URL of Webpage
with Persona Tag
<html>
<head>
<title> Persona Test </title>
</head>
<body>
<persona bitmap=“cartoon” ...>
<uselib url= .../>
<do name=“greet”/>
<do name=“standard”/>
<do name =“speak”
args=“hello”/>
</persona>
</body>
</html>
PET Application
Server
PET
Parser
PET
Generator
<html> ...
<APPLET
archive=“personaplayer.jar”...
</APPLET>
...</html>
Persona Scripts
waitscreen 4
gesture greet 0 0 null
gesture laugh 0 0 null
...
Persona Engine
Behavior Monitor
Audio Data
Event
Handler
Character
Composer
© W. Wahlster, DFKI
The Bidirectional Control Flow on
Persona-Enabled Webpages
Triggers
actions of the Persona
l Text Input
l Speech Input
l Menu Input
l Direct Manipulation
Input
Web Persona
l Mouse Clicks
l Mouse Movements
Triggers
operations on elements
of the webpage
© W. Wahlster, DFKI
Porsche 9 11 & Boxter
© W. Wahlster, DFKI
Persona Active Elements (PAE)
l
Active Images
An active image starts a persona action when clicked.
<ACTIVEIMAGE SRC=“image” HREF=“url” NAME=“image name”
STATUS=“status message” ALT=“tooltip” CACTION=“persona action onClick”
OACTION=“persona action on MouseOver” ...>
l
Addressable Objects
An addressable object is an object which can be addressed and
manipulated by Persona via its name and its position.
<PDIV DIVNAME=“name of the element” DVFRAME=“frame name”
TOP=“anchor-y” LEFT=“anchor-x”>some HTML elements</PDIV>
© W. Wahlster, DFKI
A Virtual Sales Agent for OTTO – World’s
Largest Tele-Ordering Company
© W. Wahlster, DFKI
DFKI’s Ecommerce Presentation Planner has been
extended to accommodate for various target platforms
through the introduction of a mark-up language layer
Presentation Planner
PETPML
PET
Persona
Player
Agent
Script
MS-Agent
Controller
SMIL
SMIL
Player
WML
WMLBrowser
© W. Wahlster, DFKI
Information Extraction Agents
• Information Filtering
• Information Retrieval
• Information Integration
identify relevant
documents
– ...
– identify and extract relevant
pieces of information
– transform them into canonical form
wrappers
wrappers
• operational descriptions of a target concept
• abstract from concrete occurrence within document
• robust against modifications
© W. Wahlster, DFKI
Use of a Life-like Character for Electronic Commerce
Digital Assistant Selector
© W. Wahlster, DFKI
Simulated Dialogues as a Novel Presentation
Technique
• Presentation teams convey certain rhetorical
relationships in a more canonical way
– Provide pros and cons
• The single presenters can serve as indices which help
the user to classify information.
– Provide information from different points of view, e.g.
businessman versus tourist
• Presentation teams can serve as rhetorical devices that
allow for a continuous reinforcement of beliefs
– involve pseudo-experts to increase evidence
© W. Wahlster, DFKI
Presentation Teams for Advanced ECommerce
I recommend you this SLX
limousine.
© W. Wahlster, DFKI
Underlying Knowledge Base
• Representation of domain
– FACT attribute car_1 consumption_car_1
• Value dimensions for cars adopted from a study of
the German car market
– safety, economy, comfort, sportiness, prestige, family
and environmental friendliness
– FACT polarity consumption_car_1 economy negative
• Difficulty to infer implication of dimension on attribute
– FACT difficulty consumption_car_1 economy low
© W. Wahlster, DFKI
Example of a Dialogue Strategy
Question:
How much gas does it consume?
Answer:
It consumes 8l per 100 km.
Negative Response:
I’m worrying about the running
costs.
Dampening Counter:
Forget about the costs.
Think of the prestige!
Header:
(dampening_counter ?agent ?prop
?dim)
Constraints:
(*and*
(positive ?agent)
(pol ?prop ?other_dim
positive))
Inferiors:
(Speak ?agent
(“Forget about the ” ?dim “!”))
(Speak ?agent
(“Think of the ” ?other_dim “!”))
© W. Wahlster, DFKI
Current and Future Work: Multiple Interface Agents for
User-adaptive Decision Support
User-Adaptive Search Planning
...
...
weighted propositions
Multiple Decision Support Agents
Spare parts for this car
are rather expensive!
But, it’s
fast!
© W. Wahlster, DFKI
Personified Agents Increase the User's Trust in
the System's Presentation
Experimental evidence for effects of modality on the user's trust (van Mulken, 1999)
The system gives recommendations, which turn out to be wrong in some cases.
How much does a user trust the system's advice depending on the modality of
a presentation?
1.0
0.8
0.7
0.6
0.5
Self-animated Persona,
Speech,
Speech, Gesture, Facial Graphical
Expression, Pointing Highlighting
Text,
Graphical
Highlighting
© W. Wahlster, DFKI
Impact of the modality of a Presentation on the
User's Trustfulness
Result:
Persona > Speech > Text
Conclusion: If the presentation is more human-like,
recommendations are more readily followed
For l decision support systems
l tutoring systems
l recommendation systems
l virtual sales agents
personified interface agents have a clear advantage:
They increase the user's trust in the information presented
by the system
© W. Wahlster, DFKI
Sending Interface Agents to Clients: Plug-Ins or Applets?
Plug-Ins
l
l
l
l
l
Add features (character players) to browser
Download triggered by user
Requires disk space on client
Unrestricted access to client
Less appropriate for WebCommerce,
Guides
l Agents integrated in 3D environments
l Appropriate for Entertainment
Examples:
l Extempo's Jennifer James
(Hayes-Roth et al. 98)
l PFMagic's virtual petz
Applets
l
l
l
l
l
l
l
Java animation code sent over the net
Automatic loading
Requires no disk space on client
Restricted access to client
Appropriate for WebCommerce, Guides
Agents integrated in 2D environments
Less appropriate for Entertainment
Examples:
l DFKI's Web Persona
(Müller et al. 98)
l ISI's Adele (Johnson et al 98)
New in AiA/PAN: Balanced combination of Applets and Servelets
Efficient distribution of client-side Java and server-side Java for driving the
Interface Agent
© W. Wahlster, DFKI
Research on Personalized Interface Agents brings
disparate subfields in the area of intelligent systems
together
Planning
User
Modeling
Knowledge
Representation
Image
Understanding
Personalized
Intelligent
Natural Language
Interface
Web
Agents
Understanding
Services
Machine
Learning
Plan
Recognition
Information
Multimodal Retrieval
User
Interfaces
© W. Wahlster, DFKI
Conclusion
ECommerce projects of DFKI have shown that research on personalized
interface agents can be transferred to real world applications:
Dekra (largest European organization of used car dealers):
FairCar as an ECommerce platform with NL access and a comparison
shopping agent for used cars
DaimlerChrysler: online user modelling in a one-to-one marketing system
for Mercedes cars
Otto/Shopping24/Eddie Bauer (largest European tele-order company):
virtual sales agents for one-to-one marketing of fashion and computer
hardware
Porsche: Virtual Market for Pre-owned Porsche Cars
© W. Wahlster, DFKI
Conclusion
The generation of virtual webpages with personalized interface
agents leads to innovative applications in:
Electronic Commerce, Electronic TV Guides (EPG)
Telelearning environments, Call Centers and Help Desks
Two Research Challenges:
Making the Interface agents sensitive to temporary limitations of the
user‘s time and working memory capacity (cf. our READY project,
Jameson et al., p. 79-85 in IUI99 Proceedings)
Making the agents instructible, so that they can learn from the user
in a dialog, how to extract information in a new domain (cf. Mathias
Bauer, Dietmar Dengler TrIAs: Trainable Information Assistants for
Cooperative Problem Solving in Agents'99, on Tuesday)
© W. Wahlster, DFKI