Market-specific inferencing

Finding all the potential markets for an agent to trade in requires that the Auction Manager employ not only the taxonomy of good descriptions and market operators; it also needs to know whether the agent wants to buy or to sell a particular good.

To see why this is necessary, consider two agents, one who wishes to buy a query planning service for High School audience for Astronomy topics and one who wishes to sell it. Note that in these descriptions we refer back to the simplified version of the audience and topic attributes taxonomy shown in Figure 1. In table form this service description looks like:

Service 2c|Service Attributes

Audience Topic

$$\begin{picture} (10,10) \put(5,3){\circle{10}} \put(1,-1){B}\end{picture}$$ Query Planning High School

We represent the Astronomy topics as buyer's choice because that makes the most sense for a query planning service. Since High School has no subclasses under it, it was not necessary to use an operator to describe how it is bundled. Next, suppose that Markets 1-6 in table 1 already exist. Notice that these markets may include additional attributes, such as Recommending-Organization, which were not specified in the agent's service description. Similarly, the markets may also lack attributes which are specified by an agent.

Both buyers and sellers could participate in Market 1, since it exactly matches the service description. However, in Markets 2-6, whether an agent can participate depends on the trading context (i.e., whether the agent wants to buy or sell the good).

In Market 2, the seller cannot participate since it has not been recommended by Astronomy Today. On the other hand, whether a service has been recommended or not is irrelevant to the buyer, so it can participate.

In Market 3, a buyer can always choose High School audience among the different kinds of School audiences offered. However, the seller's service is limited to High School audiences and it cannot participate in a School audiences market because buyers might want to select Middle School audience or Professional audience.

In Market 4, a seller can participate since Astronomy is a Science and the seller has the right to choose which kind Science it provides--in this case the seller would always choose Astronomy. However, if a buyer were to participate, the query planning service the buyer got matched with might very well be for Biology rather than Astronomy.

In Market 5, a seller who can offer any Astronomy subtopics, can simply unbundle the Astronomy subtopics and offer Black Holes separately. On the other hand, a buyer interested in Astronomy topics may not want to confine its queries to Black Holes but may be interested in Quasars also.

Lastly, in Market 6, the seller can participate in a market with unspecified audiences, since buyers haven't specified (don't care) what kind of audience the query planning service is aimed at. However, a buyer who specifically wants a High School audience cannot.

The informal rules expressed in the example above can be captured and used by the Auction Manager to automatically match potential markets.

 

Rule Example Operator₁[class]

$$\rightarrow Operator_2[superclass]$$

$$\begin{picture} (10,10) \put(5,3){\circle{10}} \put(1,-1){B}\end{picture} \rightarrow \begin{picture} (10,10) \put(5,3){\circle{10}} \put(1,-1){B}\end{picture}$$ When buying:

$$\begin{picture} (10,10) \put(5,3){\circle{10}} \put(2,0){S}\end{picture} \rightarrow \begin{picture} (10,10) \put(5,3){\circle{10}} \put(1,-1){B}\end{picture}$$

$$\bigotimes \rightarrow \begin{picture} (10,10) \put(5,3){\circle{10}} \put(1,-1){B}\end{picture}$$

$$\bigodot \rightarrow \begin{picture} (10,10) \put(5,3){\circle{10}} \put(1,-1){B}\end{picture}$$

$$\begin{picture} (10,10) \put(5,3){\circle{10}} \put(1,-1){B}\end{picture} \rightarrow \begin{picture} (10,10) \put(5,3){\circle{10}} \put(2,0){S}\end{picture}$$ When selling:

$$\begin{picture} (10,10) \put(5,3){\circle{10}} \put(2,0){S}\end{picture} \rightarrow \begin{picture} (10,10) \put(5,3){\circle{10}} \put(2,0){S}\end{picture}$$

$$\bigotimes \rightarrow \begin{picture} (10,10) \put(5,3){\circle{10}} \put(2,0){S}\end{picture}$$

$$\bigodot \rightarrow \begin{picture} (10,10) \put(5,3){\circle{10}} \put(2,0){S}\end{picture}$$ Operator₁[class]

$$\rightarrow Operator_2[class]$$

$$\begin{picture} (10,10) \put(5,3){\circle{10}} \put(2,0){S}\end{picture} \rightarrow \begin{picture} (10,10) \put(5,3){\circle{10}} \put(1,-1){B}\end{picture}$$ When buying:

$$\begin{picture} (10,10) \put(5,3){\circle{10}} \put(1,-1){B}\end{picture} \rightarrow \begin{picture} (10,10) \put(5,3){\circle{10}} \put(2,0){S}\end{picture}$$ When selling:

$$\rightarrow$$ When buying:

$$\rightarrow$$ When selling:

For example, the Generalize Attribute Class rule in Table 3 says that a buyer who wants topics on Astronomy, can be satisfied in a market for buyer's choice Science. Similarly, a seller who sells seller's choice topics in Astronomy, can sell in a seller's choice market for Science topics--for any customer, the seller can always choose Astronomy as the topic. By writing potential trades between markets as transformation rules, we can use forward and backward chaining to ask questions, such as what are all the potential ways that this product could be sold.

These rules model how agents can bundle and unbundle goods and choose from among bundled goods. However, there is no guarantee that these rules will terminate. In practice, both the number of markets and the existing UMDL ontology are sufficiently small that this has not been an issue. In the future, we will need to place restrictions on the rules of inference to be able to guarantee termination. Similar problems for automatic checking of security protocols using formal logics were addressed by an automatic theory-checker generator [12].