Agent-mediated electronic commerce Carles Sierra IIIA-CSIC Barcelona

1. Agent-mediated electronic commerceCarles SierraIIIA-CSICBarcelona

2. Tutorial plan Context Agents and eCommerce Mechanisms Example: The fishmarket Example: Robot Navigation Negotiation Argumentation Electronic Institutions Future trends

3. Context

4. Electronic malls Portals: aggregate information and commerce resources, add services Auction-centred sites Vertical markets/portals Wholesale, consumer aggregation Differentiation: B2B, B2C, C2C Latest growth: B2B vertical markets eCommerce evolution

5. 17 million users in 1992 195 million users world-wide in 1999 Disparity: Sweden 40.9%, Italy 8% of usage Users already sampled buying over the web (f.i. 40% in the UK) Many regular shoppers (f.i. 10% in the UK) Internet growth

6. Disparity Shoppers in Europe Revenue 1999 Shoppers 2002 Revenue 2002 Finland 20 times more than Spain. 5.2 million EUR3,032 million 28.8 million EUR57,210 million Expenses produced

7. C2C auctions: eBay Consumer to consumer auctions Services: auction engine, reputation management Revenue source: advertising, auction commissions B2C: amazon Catalog-based buying, auctions Services: transactions, delivery, recommendation Revenue source: advertising C2B: priceline Reverse auction B2B: chendex, partMiner, metalsite Catalog, auction Revenue source: membership, per-transaction fees. Examples

8. The market is Internet! Sellers. Usualy electronic, automated sites Buyers. Not automated, humans. Third parties. Few. Limited services (shopbots) Buying is based on buyers visiting sellers. eMarketplaces Protocols: Single attribute auctions (several types) Buying from catalog Reverse auctions Current eMarkets

9. One buyer, one seller (1:1) A buyer interacts with a single seller at a single site Trade has no regard to other buyers and sellers Example: buying a book at amazon.com Many buyers, one seller (N:1) Many buyers visit a single sales site Trade depends on other buyers (auctions) One buyer, many sellers (1:M) A buyer visits multiple sites simultaneously Negotiation is possible. No regards to other buyers Many buyers, many sellers (N:M) Many buers visit many sites Coordination is possible Many buyers and sellers visit a single site (exchange) Buyers/Sellers relationship

10. Single point: a market is a single meeting point for buyers and sellers Time spending: buyers are willing to spend time. Limited privacy: buyers are willing to surrender private information to sellers Price dominance: price is the main affector of buying decisions. No collusion: buyers/sellers do not collude. Familiarity: buyers can locate needed sellers. Interoperability: all sites understand each other eMarketplace assumptions

11. Single point: electronic trade takes place at multiple sites, possibly inter-correlated; buyers may have myriad alternative markets. Time spending: buyers prefer to reduce time spent. Limited privacy: buyers may prefer not to reveal private information. Price dominance: other attributes are important too: delivery, quality recommendations, etc. No collusion: human players may not collude (but electronic ones may). Familiarity: buyers do not necessarily know sellers and how to find them across markets. Interoperability: each site is developed by a different company with possibly different ontologies. Do assumptions hold?

12. Buyers’ mechanisms for participating in multiple markets (1:M), selection of better ones Efficient mechanisms for locating markets, sellers, other buyers Interoperation standards: language, protocol, ontology Buyer tools for time-efficient buying Seller tools for dynamic pricing, promotion Buyer, seller negotiation protocols and strategies Enforceable, or self-enforceable contracts Trust mechanisms Means for payment and goods’ transaction Means for secure transactions Mechanisms for keeping players’ privacy Tools for analyzing market performance Protocols and tools for N:M interaction and trade. Needs

13. Agents and eCommerce

14. Autonomy. Agents work proactively, reactively and independently of human intervention. They can wait for good deals without diverting our attention. Personalisation. Agents can be equipped with a personal profile to reflect preferences. Social ability. The communication ability of agents can be used to negotiate over prices, services and transactions. Intelligence. Agents can learn and hence perform better over time. In EC scenarios this may equate to making more money. Many AI techniques can be applied. Why Agents may help EC

15. Product brokers: Jango PersonaLogic Firefly Merchant brokering Bargainfinder, Jango, Kasbah Buyer broker Eyes. Negotiation through trusted third parties Kasbah, Auctionbot, Fishmarket Agents in ecommerce Basic limitation: Only price brokering. No product differentiation.

16. Jango & PersonaLogic Two examples

17. A personal seller is (usually) an animated character that uses conversational interactions to help a customer to use an electronic commerce site. It suggests products acording to a user profile and to his/her preferences. It helps as an answer to a user demand or proactively. It can be adapted through learning. Personalized seller

18. Ad-hoc applications Contract allocation. MAGNET. Power load management as a computational market. Control of shipment processes (EDI). Maquiladora. Generic applications Auctions Auctionbot Fishmarket Virtual markets Kasbah Bazar Metamall MAS for eCommerce

19. Mechanisms Voting Auctions Bargaining

20. Agents inhabiting the same environment need to co-ordinate their activities to improve their individual or collective performance. The aim of DAI is to design intelligent systems that behave efficiently. A common assumption in many applications, specially in AMEC, is that agents are self-interested and utility maximisers. In others, agents are co-operative. DAI is divided in two big areas: Distributed problem solving, where the designer determines the protocol and the strategy (relation between state and action) of each agent, and Multi Agent Systems, where the agents are provided with an interaction protocol but chose the strategy to follow. Introduction

21. Social Welfare: Is the addition of the utilities of all the agents for a given solution. It is a global measure a bit controversial given the difficulty in comparing the different utility functions. Pareto efficiency: A solution x is pareto efficient if there is no other x’ such that some agent improves without anyone else losing utility. It is also a global measure. Solutions that maximise the social welfare are a subset of those pareto efficients. Individual rationality: The participation of an agent in a negotiation is rational if the benefit it gets from the negotiated solution is not smaller that the benefit of not negotiating. A mechanism, or protocol, is individualoly rational if the participation is rational for all agents. Only such mechanisms are feasible. Protocol Avaluation Criteria

22. Stability: A protocol is stable if it is designed in such a way that motivates (selfish) agents to behave in a particular way. Those behaviours are called dominant strategies. When the preferred strategy for an agent depends on the strategies of others we have other criteria for stability: Nash equilibrium: Strategies S*(A)=<S*(1), ...,S*(|A|)> are in equilibrium if for each agent i, S*(i) is the best strategy suposing that the others follow <S*(1), ...,S*(i-1),S*(i+1), ...,S*(|A|)> In many ocasions there is no equilibrium, in others, there are several. Moreover, agents can form coallitions to deviate from the behaviour in the equilibrium. Also, eficiency and stability may conflict. For example (prisoner’s dilema): C D C 0,5 3,3 D 1,1 5,0 Protocol Avaluation Criteria

23. Computational eficiency: Mechanisms should be designed in a way that gives the minimum computational cost to the agent. Distribution and communication: Distributed protocols are preferred to centralised ones because they are more robust. A trade-off with the amount of communication must be found. In this introduction we’ll survey three coordination mechanisms: Votings Auctions Bargaining Protocol Avaluation Criteria

24. In a voting all agents give an input to a mechanism and the result of the mechanism is a solution for all agents. A, Agents, O, Outcomes, every agent has a preference relation over O, (>1, ..., >|A|). We want a >* that represents the social preference, and that satisfies: 1) >* should exist for all sets of inputs. 2) >* Should be defined for all pairs o,o’ d’O. 3) >* Asimetric and transitive. 4) The result should be pareto efficient: if for all i o >i o’ then o >* o’. 5) The schema should be independent of irrelevant alternatives. 6) No dictators! That is, there must be no i such that o >i o’ implies o >* o’ independently of the others. Theorem [Arrow] No election rule satisfies all requirements. Votings

25. The different voting mechanisms relax some of the points. Unfortunately the sixth is very often relaxed. Usually the first one is relaxed. By relaxing the third we have the plural protocol (the usual in democratic systems). By introducing an irrelevant alternative we may get that a less prefered outcome wins. The binary protocol, on top of this problem it also gives different results depending on the order of the pairings. Relax

26. Another example is the Borda protocol, that assigns |O| points to the most preferred alternative, |O|-1 to the next, and so up to the last. Points are added up and the alternative with more points wins. With this protocol we can also have some paradoxes when we eliminate one alternative. The design of social mechanisms tries to define them in a way that no one cheats. For instance, random choice. More relax

27. Auctions are mechanisms very frequent in MAS. They have been deeply analysed by economists. There are three types: 1) Of private value, e.g. a cake. 2) Of common value, e.g. treasure bonds. 3) Of correlated value, e.g. contracts. Protocols: English. If it is of private value, the strategy is to increase the bids until the reserve price. In those of correlated value the auctioneer may increase the price in predetermined amounts. Sealed bid. There is no dominant strategy. Dutch. Equivalent to sealed bid. They are very efficient. Vickrey. The dominant strategy is to bid for the reserve price. Auctions

28. A centralized protocol: one auctioneer and many buyers The auctioneer puts a good for sale. Goods can sometimes be bundled or may have different attributes The buyers make offers The auctioneer determines who wins Auctions

29. Usually easier to prevent bidder lying Simple protocol Centralized: a single point of failure Allows collusion “behind the scenes” May favour the auctioneer Auctions: pros and cons

30. Bidders free to raise their bid End: no more raises, winner: highest bidder at bid Strategy: a series of bids, based on private value, estimates of others’ valuations, their past bids Dominant strategy: bid a small amount more than current highest bid, stop when private value reached For correlated value, auctioneer increases price by constant or other rate English

31. Each bidder submits a bid not knowing others’ Highest wins, pays his bid Strategy: function of private value and beliefs about others’ valuations No dominant strategy. Best: bid less than true value How much less? Nash is computable if probability distribution of agents’ values is known Example: n agents, uniform value distribution, agent i has value vi, there is Nash if each agent i bids vi(n-1/n) First-price sealed-bid auction

32. The auctioneer lowers the price until a bidder takes it The first bidder to speak takes it Strategy: equivalent to first-price sealed bid Advantage: auctioneer can do it fast! Dutch auction

33. Each bidder submits one bid, not knowing others’ The highest bid wins but pays the second price Strategy: base bid on private value and beliefs about others’ values Dominant strategy: bid true valuation If bids more and this increment made him win, the agent may end up with a loss, since it may pay more than its true value If it bids less, there is a smaller chance of winning, and the winner may end up paying less than his true value Therefore: bid true value regardless of others Vickrey (second-price sealed-bid)

34. Computation criterion. Auctions with dominant strategies (Vickrey and English) are more efficient - no need to speculate regarding other bidders. Auctioneers revenue: Second-price is less than the true price, however first price bidders under-bid. Which effect is stronger? For risk-neutral bidders with private independent values, the effects are equivalent For risk-averse bidders, dutch and first-price sealed-bid auctions maximize auctioneer’s revenue So, are revenues equivalent? Which auction to choose

35. In real auctions, values are not private As a result, for 3 or more bidders, English auctions provide auctioneer revenue higher than Vickrey does Explanation: when it observes other bidders increasing their bid, a bidder increases its own valuation Both English and Vickrey are better for the auctioneer than Dutch and first-price sealed-bid. Real auctions

36. Bidders can coordinate their bids to lower them In English and Vickrey auctions collusion is dominant! Example. Agents a, b and c values of the good are 10, 10, 12, respectively They can agree to bid 5, 5, 6, respectively If one defects, all observe that, and can increase to real value, so there is no benefit from defection Collusion

37. In the first-price sealed-bid and Dutch auctions, bidder collusion is not dominant, but possible: In the previous example, after a, b, c decided on 5,5,6 it is beneficial for a, and b to bid more than 5. For any bid of c below 10 they can bid and win. In sealed bid, Dutch and Vickrey all bidders must identify each other and collude jointly. External bidder can win. In the English auction identifying is through bidding. Computerized anonymization can prevent identification and collusion. Avoiding collusion

38. Private value auctions Vickrey: auctioneer can overstate the second highest bid to the winner Solution: electronic signature Non-private value English: auctioneer can use shills that bid in the auction to increase real bidders valuation Any auction: auctioneer may bid, to guarantee a minimum price Insincere Auctioneer

39. In private or common value auctions, the four types of protocol are pareto eficient, they assign the resource to the buyers that value them most. English and Vickrey are more efficient because they have a dominant strategy. Buyers don’t need to think on what the others are going to do. Theorem (revenue equivalence) The four protocols produce the same revenue to the auctioneer in auctions of private value with the values distributed independently and with risk-neutral buyers. The protocols are not completely protected against buyer coalitions, although sealed bid and Dutch do not favor collution. The electronic versions of the protocols go against collutions because they may avoid the mutual identification of buyers. Revenue

40. In bargaining, agents may make deals that are mutually beneficial, but they are in conflict over which deal to chose. Negotiation mechanisms fall mainly on strategic bargaining. Axiomatic Theory. The desired solutions are not those found in a certain equilibrium, but those that satisfy a set of axioms. Classical axioms are those of Nash: outcome u*=(u1(o*), u2(o*)) must satisfy: Invariance: The numerical utilities of agents represent ordinal preferences, numerical values don’t matter. Anonimity: Changing the labels of the players does not affect the outcome. Independence of irrelevat alternatives: if we eliminate some o, but not o*, o* is still the solution. Pareto eficiency: we cannot give more utility to both players over u*=(u1(o*), u2(o*)). Nash bargaining solution: o*=arg maxo [u1(o)- u1(ofallback) ] [u2(o)- u2(ofallback) ] Bargaining

41. Strategic Theory: No axioms on the solution are given, the interaction is modelled as a game. The analysis consists on finding which strategies of the players are in equilibrium. It explains the behaviour of utility maximisers better than the axiomatic theory (where the notion of strategy does not make much sense). The theory of negotiation is basically here. Without assuming perfect rationality, the computational costs of the deliberation and the potential benefits of bargaining conflict. AI (and Agents) has many things to say on this task. Bargaining

42. In bargaining, agents may make deals that are mutually beneficial, but they are in conflict over which deal to chose. Negotiation mechanisms fall mainly on strategic bargaining. Axiomatic Theory. The desired solutions are not those found in a certain equilibrium, but those that satisfy a set of axioms. Classical axioms are those of Nash: outcome u*=(u1(o*), u2(o*)) must satisfy: Invariance: The numerical utilities of agents represent ordinal preferences, numerical values don’t matter. Thus, the utility functions must satisfy that for any f linear and increasing: u*(f(o), f(ofail))=f(u*(o, ofail)) Anonimity: Changing the labels of the players does not affect the outcome. Independence of irrelevat alternatives: if we eliminate some o, but not o*, o* is still the solution. Pareto eficiency: we cannot give more utility to both players over u*=(u1(o*), u2(o*)). Bargaining

43. Strategic Theory: No axioms on the solution are given, the interaction is modelled as a game. The analysis consists on finding which strategies of the players are in equilibrium. It explains the behaviour of utility maximisers better than the axiomatic theory (where the notion of strategy does not make much sense). The theory of negotiation is basically here. Without assuming perfect rationality, the computational costs of the deliberation and the potential benefits of bargaining conflict. AI has many things to say on this task. Bargaining

44. An application: The FishMarket

45. Fish Auction in Blanes ‘Llotja’ BUYERS’ ADMISSION SELLERS’ ADMISSION AC AV Buyers registration Fish and sellers registration AUCTIONEER S Fish show and auction SELLERS’ SETTLEMENTS BUYER’S SETTLEMENTS Fishermen payments Fish delivery and payment GV GC

46. Virtual fish auction

47. Auction boss • Activates the FishMarket and controls all auctioning process. It may intervene talking to other agents. Closes the auction and shuts down the program. • He customizes the program

48. Auction boss Sets the auction parameters

49. Auction boss Controls the auction and closes the it whenall processes are dead.

50. Fish admission • The fish admissor interacts with the program through a browser i has the following functionalities • Input the fish characteristics for its identification and packaging • classification in boxes • Initial price setting