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The intuition is that D a t a b a s e is a set of formulae that is 'agreed' between the agents participating in the argumentation process This database provides some common ground between the agents Given this common ground, an agent makes the argument (Sentence, G r o u n d s ) in support of the claim that S e n t e n c e is true; the justification for this claim is provided by G r o u n d s , w h c h is a set of formulae such that S e n t e n c e can be proved from it.

. ,2B - 1, adapt its coefficients:

= E (a small positive number),

Formally, if A is a database, then an argument over A is a pair (cp, T),where p is a formula known as the conclusion, and r r A is a subset of A known as the grounds, or support, such that r I- cp We denote the set of all such arguments over database A by A ( A ) , and use A r g , A r g ' , A r g , , to stand for members of A(N Typically an agent will be able to build several arguments for a given proposition, some of which will be in favour of the proposition, and some of which wdl be against the proposition (in which case they are for its negation).

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The major shortcoming of memory parity is that it can only detect an error. Parity mechanisms don t have a means of identifying specifically where or what the error is; they can only detect that a possible error has occurred. All memory parity can report is that either the even or odd bit count was wrong.

In order to establish whether or not the set of arguments as a whole are in favour of the proposition, it is desirable to provide some means of flattening the set of arguments into some measure of how favoured the proposition is One way of doing t h s is to attach a numerical or symbolic weight to arguments and then have a flattening function that combines these in a suitable way However, it is also possible to use the structure of the arguments themselves to determine how good they are We can identify two important classes of arguments as follows..

The prospect of creating multiple tables almost always intimidates beginning database users. Most often, beginners want to create one huge table that contains all the information they need for example, a customer table with all the sales placed by the customer plus the customer s name, address, and other information. After all, if you ve been using Excel to store data so far, it may seem quite reasonable to take the same approach when building tables in Access. A single large table for all customer information quickly becomes dif cult to maintain. You have to input the customer information for every sale a customer makes (repeating the name and address information over and over again in every row). The same is true for the items purchased for each sale when the customer has purchased multiple items as part of a single purchase. This makes the system more inef cient and prone to data-entry mistakes. The information in the table is inef ciently stored certain elds may not be needed for each sales record, and the table ends up with a lot of empty elds. You want to create tables that hold the minimum of information while still making the system easy to use and exible enough to grow. To accomplish this, you need to consider making more than one table, with each table containing elds that are only related to the focus of that table. Then, after you create the tables, you link them so that you re able to glean useful information from them. Although this process sounds extremely complex, the actual implementation is relatively easy.

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