1. Auctions and Multi-agent Systems
발표자 : 오 연 희

2. Purpose
Discuss how a virtual institution can be derived from the Llotja(a fish market)
Show how this institution can be applied to define other institutions where the participants can be software agents

3. Auction Auctions are price-fixing mechanisms : bidding convention
Auction houses is institutions
: also, other equally relevant conventions are used. (about registration of participants and goods, guarantees, payment, commissions, starting prices, etc...)

4. Three types of conventions
Ontologic and Communicational Conventions
Social Conventions
Individual Behaviur Rules

5. But, we are concerned with VI!!
The Difference of virtual institution from traditional auction house
- Virtual location
- software agent
Consequently, it could be understood as a multi-agent system model, or more specifically, as its computational realization in the Internet.

6. Feature of Virtual Institution
Message Exchange
strong dialogical stance
Dialogical system

7. Llotja (a fish market of Blances) : traditional auction house
Five scenes(location, staff)
1. Buyers’ register(AR, ba)
2. Goods’ register(RR, sa)
3. Goods’ show and auction(AH, auct)
4. Credits and goods delivery(DR, bm)
5. Sellers’ settlements(BO, sm)

8. Scenes in the Blanes Llotja

9. Illocutions used in an upward bidding round in the Fishmarket

10. Fishmarket bidding rounds

11. The Difference of Fishmarket from the Blanes auction
The Participants can be computer programs executed in a remote location
collisions are managed in the Fishmarket
- by a random selection of a winner

12. Institution  FM = <DF, PS, BR> Dialogical Framework
Performative Structure
: articulation of scenes
Individual Behavior Rules
 FM = <DF, PS, BR>

13. Performative Structure

14. Commitments established in an auction house
Exchange of auctioned goods
their features
the exchange conditions

15. Information structure for Commitments in the Fishmarket
The auction’s catalogue
: storage of information related to the goods auctioned
each seller’s account
: identification, the income and commissions
each buyer’s account
: credit and the purchases mode

16. Individual Behavior Rules(purpose)
The need of making these conventions explicit and more intelligible for users or external observers
To facilitate the definition and update of the institution’s conventions

17. Individual Behavior Rules(example)

18. Convention Variant of the Fishmarket 1.
Closed bidding auction
- operator(selected and creditstatus) is added and extended
Vickrey bidding : upward and closed bidding
- selected operator is changed

19. Convention Variant of the Fishmarket 2.
The same individual rules, the same illocutions and the same operators could be used for any of its variants
Use of sufficiently general operators
- parametrized

20. Compoments of Dialogical Framework for Fishmarket
Agents a set of identifiers
Rol = {boss, auct, sa, sm, ba, bm}  {s, b}
SR = {<boss, x> : x  Rol \ boss}
Loc = {AH, RR, AR, DR, BO, M}
L the “object language”
CL (a communication language)
ML (metalanguage to define behaviour rules)
T a time model

21. Models and Implementation
FM: auction house
A: auction
G: auctioned goods
A: participating agents
E0…Ew: the incidents evolve
A = <A, G, <E0..Ew>>

22. Institutions Agent-mediated institution Agent-based instutions
- “Cohabited Mixed Reality Information Space” project
Agent-based instutions
- “medical protocols” SMASH project

23. Closing Remarks #1 Artificial Intelligence
A interdisciplinary problem
other fields of AI

24. Closing Remarks #2 multi-agent systems
Constitute a non-trivial problem
a domain in which competitive evaluation is possible
auctions are a conveniently scalable problem

25. Closing Remarks #3 Electronic Commerce
Electronic exchange through the Internet
The opportunity of developing agents