Alina Pommeranz, MSc in Interactive System Engineeringsupervised by Dr. ir. Pascal Wiggers and Prof. Dr. Catholijn M. Jonker

Content

Introduction Pocket Negotiator Research Goals from HCI perspective First Experiment User-centered Approach Questions and Suggestions

About myself

Education 4-years Computer Science, FH

Gelsenkirchen, Germany 2-years Master of Science in Interactive

Systems Engineering, KTH Stockholm, Sweden

Previous Research 1 year at the Swedish Institute of

Computer Science (SICS)

Negotiation support

Negotiation is a common task,but still only few people are good negotiators

Computers can better cope with the computational complexity (many options, combinations of variables, solutions)

Negotiation cannot be handled by artificial intelligence alone (semantic problem , emotional issues involved)

Pocket Negotiator(PN) “new type of human-machine

collaborative system that combines the strengths of both [human and system] and reduces the weaknesses.” (Jonker, 2007)

The PN will handle computational complexity issues provide bidding- and interaction advice

the user will handle background knowledge interaction with the opponent negotiator

Pocket Negotiator (PN)

handheld device 2 domains:

real estate job negotiations

for non-expert users

Issues from a Man-Machine Interaction point of view Preference Elicitation

User preference model Interaction between the system and

the user (generic task model) Explanation/Training Module (use of

animated character) Visualization techniques (for small

devices)

Preference Elicitation Experiment Goal: investigate preference elicitation

techniques involving different research areas (AI, HCI, Affective Computing)

Evaluation of user satisfaction (liking, ease of use, intuitivity) with different ways of giving preferences

Holiday domain 32 participants 8 ordering/rating tasks (including affective

feedback and navigational interaction), 2 comparisons and a questionnaire

Lexicographic ordering Paper submitted to HuCom 2008

Experimental setup

activeHotell Active

Results

Traditional property rating seems most preferred and resulted in one of the best orderings of the outcomes space when using the lexicographic algorithm

Properties of holidays are interdependent for more than a 3rd of the participants

Considering affective attitude can improve understanding of users’ preferences

With a multi-angle approach we could identify limitations and issues that would have not been found with just one research perspective

How to use the results?

When designing a new preference elicitation method we need to consider dependencies of

preferences navigation task is suited to find a number of

such dependencies rating of properties should be done in

known and preferred ways (Likert scale) we could incorporate ways to express affect

to properties/outcomes a combination of different techniques might

be the way to go (needs to be tested)

Limitations of the experiment Complete ordering of holidays as

control condition small set of properties and their values Rating and ordering tasks very quick and

with little effort Strengths of other techniques in the

background

User-centered approach I

Video-supported study on social acceptance, practices and use-contexts (scenarios)

Case studies with potential users including Observation of real life negotiation situations (not

only bidding but all other phases, too) Capturing such situations on camera Maybe physiological measures (heart rate, GSR

etc. to measure emotions) Questionnaires and interviews before and after

the negotiation phases Diaries by the users

Interviews and Focus groups with experts in the domains (e.g. real estate agents, P&O members)

User-centered approach – II Design of Negotiation Scenarios based

on the case study data and used in further experiments

Iterative implementation of prototypes Wizard-Of-OZ experiments to test

(with prototypes): Preference elicitation techniques User-system interaction techniques Visualization techniques Explanation/ training module

Questions? Suggestions?

Thanks for your attention!