InfoCenters and Information E-markets Itai Yarom PhD Researcher - AI Lab

InfoCenters and Information E-markets2 Agenda Introduction and motivation The model The Experiments Results and conclusions Future research

InfoCenters and Information E-markets3 Introduction E-commerce opens up the opportunity to trade with information, e.g., single articles, customized news, music, video. E-marketplaces enable users to buy/sell information commodities. Information intermediaries can enrich the interactions and transactions implemented in such markets ( we extend the basic model presented by Kephart et al.(2000) ).

InfoCenters and Information E-markets4 What are e-markets? Market infra-structure Centralized or decentralized (P2P) market. Trading protocol How agent communicate? E.g. Web-services. Trading mechanism Post-Prices, CDA, Auction, reverse auction. Market Policies E.g., reputation mechanism. Agent strategies How do the agents decide what to do?

InfoCenters and Information E-markets5 Information E-marketplace Buyer Seller InfoCenter InfoSP I1I1 I2I2 I1I1 I2I2 & I 1 I 2 Combine Translate I 1 I 2

InfoCenters and Information E-markets6 InfoCenter Agents E-markets are extended to include InfoCenter agents and Information Services Providers (InfoSPs). Advantages: InfoCenters have wide accessibility to information commodities and can contact different information sources. InfoCenters can approach InfoSPs to obtain and sell manipulated information.

InfoCenters and Information E-markets7 Motivation When does the need for InfoCenter agents rise? When InfoCenters already exist. e.g., Stanford Digital Library Project. When the buyers benefit from them. Question answering service. When the sellers benefit from them. e.g., Kamoon (information matching service).

InfoCenters and Information E-markets8 The model The E-market contains buyers, sellers, InfoCenters and InfoSPs. The number of buyers is significantly larger than the number of sellers and InfoCenters. Each agent performs an action at a random rate (action = buy or set a price).

InfoCenters and Information E-markets9 The Buyers Compare-All (70%) Choose the seller with the lowest price. Compare-None (10%) Choose a seller randomly. Compare-Two (20%) Choose two sellers randomly and buy from the one with the lowest price.

InfoCenters and Information E-markets10 The Sellers Myoptimal (MY) Choose the optimal price at a specific time. Game Theory (GT) Choose one price from the existing mixed Nash- equilibria Deviate Follower (DF) Continue to change the price in the same direction (i.e., increase or decrease) until the profit falls under a certain value.

InfoCenters and Information E-markets11 The InfoSPs InfoSPs are Information Service Providers agents. The services can be: Different presentation formats and resolutions. Information updates. Combining and summarization. Juice making service Packaging service InfoSPs

InfoCenters and Information E-markets12 InfoCenters’ Capabilities Manipulate information InfoCenters can approach InfoSP agents in order to obtain manipulated information (e.g., combine, translate operators). Switch information InfoCenters can change the information they offer. Cooperation InfoCenters can share the information products that they offer. Intelligent InfoCenter The InfoCenter can use AI technique, as planning and approaching buyers to understand their needs.

InfoCenters and Information E-markets13 AI techniques InfoCenters can use AI techniques, including: Approach buyers in order to understand which information they interested at. Apply planning algorithms in order to use wisely the InfoSPs’ services. Share information on buyers’ preferences and on InfoSPs’ services.

InfoCenters and Information E-markets14 Utility of the Agents Who have the permission to set the market utility function? Each agent. Each agents’ creator. Each marketplace. The alternatives: 1.The sum of the agent’s profit. 2.The average of the agent’s profit. 3.The normalized average profit.

InfoCenters and Information E-markets15 Utility of the Agents (continue) Utility characteristics: Time independence. Monotonic in the profit. Monotonic in the transaction. Normalization: U:[0,1]->[0,a] when a>0

InfoCenters and Information E-markets16 Criteria for Evaluation InfoCenter profit This criterion compares the gain obtained by the InfoCenter in each one of the configurations tested. Stability of the marketplace This criterion checks the effect of the InfoCenter on market behavior.

InfoCenters and Information E-markets17 The Experiments InfoCenters operate as sellers’ assistances. How will the InfoCenters effect the e-market? InfoCenters operate as autonomous agents. What is the preferred discount method? What are the best pricing strategies? Intelligent InfoCenters. Which AI techniques can increase the InfoCenters profit?

InfoCenters and Information E-markets18 Results InfoCenters operate as sellers assistance InfoCenters that cooperate, switch or sell manipulated information are more profitable than basic ones. In homogeneous markets, switching InfoCenters are the most profitable. In heterogeneous markets, InfoCenters who sell manipulated information are the most profitable. InfoCenters will affect the market by selling at more stable prices, that are also higher on average.

InfoCenters and Information E-markets19 InfoCenters Price Behavior Basic MY Co- MY Switching MY IC MY

InfoCenters and Information E-markets20 InfoCenters’ Payment Strategies Full Price (FP) The InfoCenter pays the list-price for the information it buys. Wholesale Price (WP) The InfoCenter pays a reduced price when it buys a large quantity. Subscription Price (SP) The InfoCenter pays a subscription fee in order to obtain the information, and then royalties for all information it sells.

InfoCenters and Information E-markets21 Results InfoCenters operate as autonomous agents InfoCenters gain positive profit. The buyers and the sellers benefit from the existence of the InfoCenters. InfoCenters benefit more from the sellers price competition than from the sellers discount (available at WP and SP). The InfoCenters prefer to use MY or GT pricing algorithm over the DF pricing algorithm.

InfoCenters and Information E-markets22 Results Intelligent InfoCenters Intelligent InfoCenters are more profitable than regular InfoCenters. Planning will reduce the costs of creating new information. Therefore, planning will be more significant as long as the variety of InfoSPs is larger. Approaching buyers will enable the InfoCenters to offer more profitable information. Using several AI technique will gain higher profit as compare to using one technique.

InfoCenters and Information E-markets23 Stability of the Marketplace In most of the cases the price behavior of an e-market with InfoCenters are the same as one without them, except: When the InfoCenters cooperate or switch information. In that case, the frequent of the price change is lower. When the InfoCenter create new information. In that case, the price change of the new information is similar to the case of a market place with sellers offering that information.

InfoCenters and Information E-markets24 Request for Price Quotes (RPQ) Price sniffing (by buyers, sellers and InfoCenters) will create a load on the sellers and the InfoCenters 1. Sellers can handle the load by: Using the InfoCenter as a retailer. Ask for fee for every RPQ. Deciding when to ask for price quote should be done ‘wisely’. 1 “When bots Collide”, Kephart and Greenwald.

InfoCenters and Information E-markets25 Conclusions InfoCenters succeed to gain positive profit. Buyers and sellers gain from the existence of InfoCenters in the market: Provide more focused information to buyers. Increase the sellers transaction. Intelligent InfoCenter gain higher profit comparing non-intelligent InfoCenters. The price behavior with and without InfoCenters is similar.

InfoCenters and Information E-markets26 Future Research What is the best pricing algorithm for an agent in an information e-market? Will we get a different results when using other market mechanism (or combination of them), like auction or CDA? How decentralized market will effect the agent profit? How can InfoCenters benefit from coalition? What mechanism can be used to generate trust between the agents? And does a trustworthy agent is a good thing?

InfoCenters and Information E-markets27 More Information The Role of Middle-Agents in Electronic Commerce, (IEEE Intelligent System Journal). The Benefit of Software Middlemen in Information E-markets: An Empirical Study (Journal version in preparation). The Design of Utility Functions for Information E- marketplaces with Price Quote Fees (not published). The Impact of InfoCenters on E-Marketplaces (AAMAS’02). Pricing and Manipulation of Information in E-Marketplaces (BISFAI 2001).

InfoCenters and Information E-markets28 Reference Dynamic Pricing by Software Agents, Kephart, Hanson and Greenwald, Computer Networks (2000). Shopbots and Pricebots, Greenwald and Kephart, IJCAI-99. Middle-agents for the internet, Decker, Sycara and Williamson, IJCAI-97. Agent-Human Interactions in the Continuous Double Auction, Das, Hanson, Kephart and Tesauro, IJCAI-01.

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