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eCommerce Technology 20-751 Agents and Auctions

eCommerce Technology 20-751 Agents and Auctions. What is an Agent?. In real life, a person who acts on your behalf In eCommerce, a computer program that acts on your behalf Agents often perform tasks usually associated with humans

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eCommerce Technology 20-751 Agents and Auctions

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  1. eCommerce Technology20-751Agents and Auctions

  2. What is an Agent? • In real life, a person who acts on your behalf • In eCommerce, a computer program that acts on your behalf • Agents often perform tasks usually associated with humans • But: an agent is just a computer program with certain properties • Synonyms: • bot • daemon (a supernatural being of Greek mythology intermediate between gods and men)

  3. Agent Properties • Autonomous • Acts by itself (independent of user) • Reactive • Responds to its environment, initiates actions • Communicative • Communicates with people and other agents • Goal-driven • Acts until it accomplishes its purpose or learns that it can’t

  4. Proactive Don’t constantly need instructions Able to work unaided E-commerce/ E-business Agents Information Management Agents “Hidden” Agents Really smart Agents Cooperate Learn Share information with each other. Able to agree on subtasks Improve their actions with experience Adapt to user requirements Intelligent Agents: Key Features SOURCE: BEN AZVINE

  5. Examples of Agents • Search agents • Find web pages. FastSearch, Google • Metacrawlers • Search multiple indexes. Dogpile, MetaCrawler • News agents • Locate relevant news stories. TotalNEWS • Monitors, update agents • Notify user when events occur, e.g. page is modifiedChangeDetection, CyberAlert (company news), Enfish tracker (tracks email, web pages, files) MorningPaper • Instruction agents • How to do things. eHow (repair a roof)

  6. Information Agents • Addresses, phone numbers, reverse directories • AT&T AnyWho, BigYellow, InfoSpace (by address!) • Stock bots (financial information, charts, news) • StockPoint, Silicon Investor, biz.yahoo, 1jump • Filtering agents • Remove unwanted data not fitting profile

  7. Shopping Agents

  8. Shopping Agents • Price bots • BestBookBuys, BottomDollar, Point&Shop, PillBot (medication) • Sale locators • ShoppingList.com (brick & mortar), ValueFind • Auction notification • BidFind • Recommenders • ActiveSalesAssistant

  9. Travel Agents • Information about flights, trains, purchase tickets • USAirways, Orbitz • Discount Hotels • hoteldiscount!com • Airplanes in flight • FlightView, FlyteComm, DFW • Chicago tower

  10. Examples of Agents • Negotiation agents • Agent Builder Tools • CMU Bot List • CMU Agent Page

  11. Avatars • A simulated human being • From Sanskrit: “Earthly incarnation of a Hindu god or goddess” • Verbot

  12. Agent Technologies • Table-driven (data lookup) • Rule-based • Goal-directed • Utility-based inputs “ ”

  13. Rule-Based Agents Condition-action rule: ifcar-in-front-is-brakingthenstart-braking SOURCE: ANDREAS GEYER-SCHULZ

  14. Business Rules • Grocery store example IF inBasket(french_fries) AND NOT asked(ketchup) THEN ask(ketchup) ; ask “Would you care for ketchup to go ; with your french fries?” • Rules that learn IF inBasket(french_fries) THEN prob(want_ketchup) = SQL( <sql_query> ) ; query might involve customer data and ; demographics IF prob(want_ketchup) > 0.3 AND NOT asked(ketchup) THEN ask(ketchup)

  15. Fuzzy Logic Traditional set theory: • Set membership. If bi = 1 then ei T else ei T • S = { a, b, c, d, e, f, g } b = 0, 0, 1, 1, 0, 1, 1 then T = { c, d, f, g } b is the membership function Fuzzy set theory • The membership function can be any value in [0, 1] • Often interpreted as a probability • S = { a, b, c, d, e, f, g } b = ½, 0, 1, ¾, 0, 1, ¼ • Now what is T? (g is 25% in T, 75% not in T)

  16. Fuzzy Logic • IF temperature IS hot AND humidity IS sticky THEN air_conditioning = high • What is hot? Is 60° hot? 70°? 80°? 90°? • 60° is definitely not hot; 90° is definitely hot; everything else is “in between” hot(60) = 0; hot(90) = 1; hot(75) = 0.4 etc. • What is sticky”?80%, 90%, 100%? • Fuzzy logic hasfuzzy inferencerules, e. g.A  B = A*B HOT COLD TEMPERATURE, °F

  17. Goal-Directed Agents Actions are evaluated with respect to goals Will this action get me closer to the goal state? SOURCE: ANDREAS GEYER-SCHULZ

  18. Static Agent System Mobile Agent System Static versus Mobile Agents SOURCE: MITSUBISHI

  19. Formation Formation BusinessLogic BusinessLogic Fulfilment Fulfilment ExecutionFramework ExecutionFramework Buyer Contract Formation Contract Seller SOURCE: CHRIS PREIST, HP

  20. Formation Formation BusinessLogic BusinessLogic Fulfilment Fulfilment ExecutionFramework ExecutionFramework Buyer Event Scheduling contract and scheduleexecution Seller SOURCE: CHRIS PREIST, HP

  21. Formation Formation BusinessLogic BusinessLogic Fulfilment Fulfilment ExecutionFramework ExecutionFramework Buyer Obligation Pending An obligation is pending. Fulfilment is triggered. Seller SOURCE: CHRIS PREIST, HP

  22. Formation Formation BusinessLogic BusinessLogic Fulfilment Fulfilment ExecutionFramework ExecutionFramework Buyer Invoke Processes Processes to fulfill theobligation are retrievedand invoked Seller SOURCE: CHRIS PREIST, HP

  23. Formation Formation BusinessLogic BusinessLogic Fulfilment Fulfilment ExecutionFramework ExecutionFramework Buyer Execute Processes Processes are executed Seller SOURCE: CHRIS PREIST, HP

  24. Formation Formation BusinessLogic BusinessLogic Fulfilment Fulfilment ExecutionFramework ExecutionFramework Buyer Mark Obligation Fulfilled The obligation is fulfilled Seller SOURCE: CHRIS PREIST, HP

  25. Formation Formation BusinessLogic BusinessLogic Fulfilment Fulfilment ExecutionFramework ExecutionFramework Buyer Signal Fulfilment Notify seller Seller SOURCE: CHRIS PREIST, HP

  26. Formation Formation BusinessLogic BusinessLogic Fulfilment Fulfilment ExecutionFramework ExecutionFramework Buyer Acknowledge Fulfilment Acknowledge fulfilment Seller SOURCE: CHRIS PREIST, HP

  27. Cooperating Agents SOURCE: PETER FINGAR

  28. Networks of Agents CAMPBELL Soup Intermediate Agent Gourmet-to-Go 3 2 DB1 5 • Intermediate Agents: • Interfacing • Networking and searching • Optimal Matching 1 DB2 4 COCA-COLA Beverage Intermediate Agent • Local Objects: • Financial agent • Purchasing agent • Inventory management agent • Customer Services agent • Other objects SOURCE: MOHSEN JAFARI, RUTGERS

  29. Major Ideas • Agents are the wave of the future • laziness + information overload = agents • Agent systems are object-oriented and distributed • Agents are mobile • Agents negotiate with and talk to other agents

  30. Auctions • Process for matching buyers and sellers and setting prices. Allows supply and demand to operate • “a market institution with an explicit set of rules determining resource allocation and prices on the basis of bids from the market participants”-- McAfee & Macmillan (1987) • A protocol for exchanging bids and determining a winner • Thousands of different protocols possible, depending on auction rules • Auctions are complicated

  31. Auctions • Foreign exchange ($2T per day) • Securities ($100B per day) • Government debt • treasury bills > $1T per year, municipal bonds • Public works (roads, bridges) • Private construction • Frequency spectrum • Oil drilling rights • Fishing quotas • Cars (Japan Aucnet) • Sheep and cattle (Australia)

  32. Price Discovery • In a marketplace, how are prices set? • Slow movement toward equilibrium, called tatonnement (from French tâtonner, “to feel one’s way”) • Exchange of price information in many steps • Why? No one wants to reveal his price at the start • Could be instantaneous if prices were revealed to a neutral agent

  33. Valuations • Private value : value of the good depends only on the bidder’s own preferences • Refrigerator to be used at home • Common value : bidder’s value of an item determined entirely by independent valuation • Treasury bills • Correlated value : bidder’s value depends partly on own preferences & partly on others’ values • Manufacturing contract whose tasks can be subcontracted out • Goods for resale (art purchased by a dealer)

  34. Auction Rules • When does the auction start and end? • Who can participate? (public, registered users, trading partners) • What type of auction? • Is the number of bidders (& Identities) known? • How are bids submitted? (timing, increments) How many bids? • Can bids be withdrawn? • Who can see the bids? (open, sealed) • How is winner determined? How is price determined? • Payment terms • AUCTION RULES AFFECT THE FINAL PRICE

  35. English Auctions • One item, one seller, multiple bidders • Bidders call out increasing bids • Auction ends when bidding stops • What price will win this auction? • Private values: $10, $17, $18, $20, $23 • Answer: the smallest bidding increment over the second-highest bid • NOT the maximum anyone is willing to bid

  36. Dutch Flower Auction • Many items, one seller, multiple bidders • Price declines with time according to a clock • First bidder to accept a price wins the auction, buys the quantity he wants • Auctioneer resets the price clock, restarts • Price tends to go up as supply decreases • Very fast, often used for perishables: flowers, fish

  37. Dutch Flower Auction Clock SIMULATION ONTARIO AUCTION WEBCAM SOURCE: BADM.SC.EDU

  38. Fish Auction FISH AUCTION SOURCE: ALLOT.COM

  39. Single Sealed-Bid Auctions • One item, one seller, multiple bidders • Bidders each submit ONE bid, which they cannot withdraw • The highest bid wins • If a bidder values the item at $v, how much should he bid? • ANSWER: less than $v, depending on the number of bidders and his estimate of the behavior of other bidders

  40. Sealed-Bid Second-Price(Vickrey) Auctions • One item, one seller, multiple bidders • Bidders each submit ONE bid, which they cannot withdraw • The highest bid wins, but the price paid is the amount of the second-highest bid • If a bidder values the item at $v, how much should he bid? • ANSWER: exactly $v

  41. Revenue Equivalence Theorem • William Vickrey (1961) • The following auction rules produce the same theoretical revenue for the seller if buyers are risk-neutral in a private-value auction: • English • Dutch (one item) • single sealed-bid • second-price sealed-bid (Vickrey) • Nobel Prize, 1996

  42. Trading Rules of a Double Auction BUYERS SELLERS 5.1 4.1 2.8 2.4 1.6 highest 5 4 3 2 1 PRICE: 2.9 PRICE: 3.2 lowest PRICE: 3.3 Trading price = (buy price + sell price) / 2 Highest buyer matched to the lower seller, 2nd highest buyer is matched to the 2nd lowest seller, etc. Condition: buy price  sell price SOURCE: JUNLING HU

  43. NASDAQ • National Association of Securities Dealers Automated Quotations • 61,000 computers • 6500 stocks • Continuous double auctions (CDA) • ARCA Integrated Book

  44. Some Auction Types Auction Double-sided Single-sided Outcry Sealed-bid Outcry Sealed-bid Call Market Synchronous Descending Ascending Asynchronous First Price or Vickrey Clearing House CDA English Dutch CDA = CONTINUOUS DOUBLE AUCTION, E.G. NEW YORK STOCK EXCHANGE SOURCE: JUNLING HU

  45. eAuction Types Used in Practice SOURCE: BEAM & SEGEV

  46. AuctionTypes SOURCE:LAUDON & TRAVER

  47. Buyer register alert search display bid Pref. notify Short list select notify auction Registration Pref.& Target Product Auction Rules START bids Delivery & Payment evaluate define cancel offer END target update update Setup auction select register auction Seller registration Product description & auction setup Auction close & evaluating bids bidding Online Auction Structure SOURCE: JERRY GAO

  48. Major Ideas • Auctions are the most important market mechanism • Primarily an information exchange protocol • Very complicated: small changes to rules cause large changes in behavior • Agents can be used in auctions

  49. Q A &

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