Outline. Protocols, Strategies and Architectures for Automated Negotiation. Claudio Bartolini HP Labs Bristol Bologna, November 17, 2000

Transcription

1 Protocols, Strategies and Architectures for Automated Negotiation Claudio Bartolini HP Labs Bristol Bologna, November 17, 2000 Page 1 Outline Part I Definition of the Negotiation Process Part II Importance of Negotiation in the New Economy Part III Negotiation Protocols and Strategies Part IV Agent-based Software Architectures for Negotiation Page 2

2 Part I - Definition of the Negotiation Process Page 3 Negotiation A UHJXODWHGSURFHVV, aimed to the formation of an DJUHHPHQW among the SDUWLFLSDQWV to the process Page 4

3 Negotiation Protocols The set of rules which govern the interaction: Permissible types of participants (negotiators and third parties Negotiation states (accepting bids, negotiation closed) Events that cause states to change (no more bidders, bid accepted) Valid actions of participants in particular states (which messages can be sent by whom, to whom, at what stage) Page 5 Examples of negotiation One to one bargaining Auctions Request for quotes (RFQ) Page 6

4 Part II - Importance of Negotiation in the New Economy Page 7 Commerce meets the Web First generation E-Commerce Amazon.com, E-Bay, Priceline.com Second generation E-Commerce B2B Exchanges: e-steel, PaperExchange Page 8

5 Importance of Negotiation Business-to-Business trading needs negotiation Negotiation can be multi-party Difficult to automate Page 9 The difference between auctions and negotiation mechanisms has blurred with the arrival of the Internet and E-Commerce Are all E-Commerce Negotiations Auctions? Are auctions negotiations? Are negotiation auctions? Mechanisms such as logrolling and simultaneous improvements are not easily expressed in auction theory Our argument: auctions can be seen as negotiation, whereas there s more to negotiation than what can be expressed in an auction framework Page 10

6 Dimensions of Complexity in Negotiation Mechanisms Multiple parameters of the good/service being negotiated over Multiple goods sold/bought Page 11 Mechanisms One-to-one One-to-many (auctions, reverse auctions) Many-to-many (double auctions) Page 12

7 Multiple Parameters Not only price Pricing policy Delivery procedure Timing constraints Payment methods Page 13 First generation E- Commerce Sales via the Internet have increased dramatically Some companies (Amazon) sell only via the Internet Other companies use the net as a marketing tool Page 14

8 E-bay Most famous Internet Auction Site Not only auctions: Free insurance Escrow service Traders rating service Authentication Investigation Dispute resolution Page 15 Priceline.com Buyer make their own price, sellers will match Airline tickets, hotel rooms Page 16

9 Agents in Electronic Commerce First generation: Focussed primarily on consumer trading Second generation: realize that negotiation is important for business to business Page 17 Stages in Trading What do I need? What products provide this? Where can I buy them? At what price? How do I pay? How will it be delivered? What post-sales support can I get? Page 18

10 Shopbots and Pricebots 6KRSERWV: agents that automatically search the Internet to obtain information about prices and other attributes of goods and services. 3ULFHERWV -- adaptive, price-setting agents which firms may well implement to combat, or even take advantage of, the growing community of shopbots. Study by Greenwald and Kephart: what does the proliferation of electronic agents induce: price wars and pricebots earning higher profits than game-theoretical equilibrium Page 19 Firefly Collaborative filtering agent Helps decide what CD or movie to buy Compares your tastes with others Proposes you try out a CD enjoyed by people with similar tastes to you Firefly was acquired by Microsoft in 1998 Page 20

11 BargainFinder The first price search agent Finds the cheapest suppliers of a given CD Some traders wanted to ban it (CDLand), others welcomed it in Page 21 SmartBidder Simple agent in internet auctions Bids on your behalf up to your maximum price Bids just above the previous bidder Page 22

12 Agent-Based Automated Trading Suppliers and consumers delegate to agents Agents negotiate with each other to determine prices Pricing is affected by supply and demand 24x7 trading based on current information agent always present Page 23 Advantages of the Web Reduced sales overhead (no shopfront) Potential international market Ease of providing large amount of information Page 24

13 Second Generation E- Commerce Business-to-Business (B2B) sales General supplies (e.g. paper, electronic components) Specialised contracts Services (e.g. contract programming, translation) Page 25 B2B E-Commerce Catalog aggregators B2B Exchanges Page 26

14 B2B Catalog Aggregators Streamlines purchasing by aggregating the product catalogues of each supplier in one place and one format Examples: e-chemicals, Chemdex, Metalsite, PlasticsNet Technology providers: Ariba CommerceOne Other 126 listed by B2BBusiness.net under the category Enablers and Builder -> Auctions and Exchanges on November 15, 2000! Page 27 A Sample Technology Provider: Trading Dynamics Bought by Ariba in 2000 for 100M$ Now commercialised as Ariba Dynamic Trade Fully integrated auction and exchange application The solution allows market participants to trade based on a broad range of factors, including price, product quality, payment terms, service levels and delivery options Other similar solutions from TradeAccess and Exterprise Page 28

15 B2B Exchanges Categories of B2B Exchanges Trading Hubs Post and Browse Auction Markets Fully-automated Exchanges Page 29 Part III - Negotiation Protocols and Strategies Page 30

16 Auction Theory and Game Theory Auction theory is a type of applied game theory that is concerned with allocation of goods if valuation of the buyers for the goods are unknown Page 31 Standard types of auction Ascending-bid auction (English) Descending-bid auction (Dutch) First-Price sealed-bid auction Second-Price sealed-bid auction (Vickrey) Page 32

17 Ascending-bid Auction Also known as English Auction Price is successively raised until only one bidder remains That bidder wins the object at the final price Its continuous version is called Japanese Auction by some economists Subject to the ZLQQHU VFXUVH: the paradox that the winning bid in an auction is greater than the product s market evaluation Page 33 Descending-bid Auction Also known as Dutch auction, so called after the flower market Price is successively lowered until a bidder calls out that they want the object at that price Page 34

18 First-Price sealed-bid auction Each bidder independently submits a single bid without seeing others bids The object is sold to the bidder who makes the highest bid The price the bidder pays is how much they bid for Page 35 Also known as Vickrey auction Second-Price sealedbid auction Each bidder independently submits a single bid without seeing others bids The object is sold to the bidder who makes the highest bid However, the price the bidder pays is the price of the second highest bid Page 36

19 Revenue-Equivalence Theorem Vickrey 1961; Regardless of the type of auction (Dutch, English, First-price sealed-bid or Vickrey), the highest price paid by a group of rational bidders is on average the same The result is based on convenient assumptions. Under more realistic assumptions, differences in the mechanisms entail difference in prices. Page 37 Multi-unit auctions Simultaneous auctions share auctions e.g. radio spectrum, TV frequencies Sequential auctions Items are sold sequentially Combinatorial auctions Bidder expresses preferences for complementary and substitutable items Complex algorithms might be necessary for winner determination Page 38

20 Reverse auctions Dual case of the auction so far presented A single buyer, rather than a single seller, controls the trading mechanism Sellers submit DVNV, rather than buyer submitting ELGV Page 39 Double auctions Buyers and sellers are treated symmetrically Buyers submit bids and sellers submit asks Structured process rather than multi-party bargaining Example: the NYSE rule Page 40

21 Agents which negotiate An agent needs A representation of the goods/services to be traded An understanding of the trader s goals (utility function) A strategy for negotiation Page 41 Utility Function A XWLOLW\IXQFWLRQ is a mathematical description of the preferences of a rational trader. The function maps alternative choices into numeric scores, such that the higher the score, the more desirable the choice Multi-attribute Utility Theory analyses preferences with multiple attributes Problems: SUHIHUHQFHH[WUDFWLRQ XQFHUWDLQW\DQDO\VLV Page 42

22 Negotiating Strategies A negotiating strategy consists in carrying out the negotiation process so as to maximise a trader s utility function, under the constraints imposed by negotiation rules and other players behaviours Multiple approaches: Rule-based Game theory Adaptive behaviour Genetic algorithms Page 43 Part IV - Agent-based Software Architectures for Negotiation Page 44

23 Weak notion of Agency (Wooldridge, 1992): Autonomy Why The Agency Paradigm Suits Negotiation No human intervention Social ability Interact with other agents Reactivity Perceive the world and react Situatedness Exhibit some goal-oriented behaviour Page 45 Wooldridge and Jennings (1995): Agent Theories Issues that developers face What is an agent Mathematical formalism to represent and reason about the properties of agents Agent Architectures From specification to implementation of software and hardware systems Agent Languages Software communication systems for programming and experimenting with agents Page 46

24 Need to define (GAIA, Wooldridge, Jennings, Kinny, 2000): Abstract concepts Agent-Oriented Software Architecture Roles Permissions Responsibilities Protocols Activities Liveness properties Safety properties Concrete concepts: Agent Types Services Acquaintances Plus: organizational abstractions (Zambonelli, Jennings, Wooldridge 2000) Organizational Rules Organizational Structures Organizational Relationships Page 47 Noriega (1997) Example: The Fishmarket Electronic Auction house Agent Testbed The Fishmarket Tournaments Page 48

25 Bibliography Negotiation N. Jennings, S. Parsons, C. Sierra, P. Faratin (2000): $XWRPDWHG1HJRWLDWLRQ, PAAM 2000 G. Kersten, S. Noronha, J. Teich (2000) : $UH$OO(&RPPHUFH 1HJRWLDWLRQ$XFWLRQV" Proceedings of COOP2000 Fourth International Conference on the Design of Cooperative Systems Page 49 Bibliography Agents in electronic commerce: M. Wooldridge (1992): 7KH /RJLFDO0RGHOOLQJRI &RPSXWDWLRQDO0XOWL$JHQW 6\VWHPV, PhD Thesis, University of Manchester M. Wooldridge, N. Jennings (1995): $JHQW7KHRULHV $UFKLWHFWXUHVDQG/DQJXDJHV$ 6XUYH\, In Intelligent Agents (ATAL 94) Page 50

26 Bibliography Agents in electronic commerce: P. Noriega (1997) $JHQW 0HGLDWHG$XFWLRQVWKH )LVKPDUNHW0HWDSKRU, PhD Thesis, Universitat Autonoma de Barcelona A. Greenwald and J. Kephart (1999) 6KRSERWVDQG 3ULFHERWV, in Proceedings of IJCAI '99 Page 51 Bibliography Agent-Oriented Software Engineering: M. Wooldridge, N. Jennings, D. Kinny (2000): 7KH*DLD 0HWKRGRORJ\IRU$JHQW2ULHQWHG $QDO\VLVDQG'HVLJQLQ $XWRQRPRXV$JHQWVDQG0XOWL $JHQW6\VWHPV, Vol 3. Number 3, September 2000 F. Zambonelli, N. Jennings, M. Wooldridge (2000) : 2UJDQL]DWLRQDO$EVWUDFWLRQVLQ WKH$QDO\VLVDQG'HVLJQRI0XOWL $JHQWV6\VWHPV, ICSE 2000 Page 52

27 Bibliography Auctions: W. Vickrey (1962) : $XFWLRQDQG %LGGLQJ*DPHV In Recent advances in game theory (pp ) Princeton, New Jersey: The Princeton University Conference P. Klemperer (1999) : $XFWLRQ 7KHRU\DJXLGHWRWKHOLWHUDWXUH In Journal of Economic Surveys (Vol 13-3, pp ) Page 53 Bibliography B2B Exchanges: A. Sculley, W. Woods (1999) %%([FKDQJHV, ISI publications Page 54