Auctions and Multi-agent Systems

1. Auctions and Multi-agent Systems 발표자 : 96419-047 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 • 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 - “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 #2multi-agent systems • Constitute a non-trivial problem • a domain in which competitive evaluation is possible • auctions are a conveniently scalable problem

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