Bratko, I. 1986.Prologprogramming for arti#cial intelligence. Addison-Wesley.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....C ) we take the set of attractor points whose address is A, compute their left inverse , take the attractor points whose address is B, compute their right inverse, in Prolog terms have a natural interpretation as trees, with the functor at the root and the arguments in the branches (c.f. [9], p.33) Because the inverse transforms are expansive, we cannot simply compute the bijective inverse transfer function on this set of points, which would give us only a subset of the actual inverses. Instead, for a given point, we compute the set of points that go to that point on the given ....

I. Bratko. Prolog Programming for Articial Intelligence. Addison Wesley, 1990. 143

....hierarchy should be constructed by a human editor to guarantee high quality, the editor can get substantial support of automatic tools. In Section 4.4 we will further discuss this matter. 4.3. 2 The Current Prototype The current prototypical implementation is in the Prolog programming language [Bra90] Because of its declarative nature, this logical programming language is very suited for handling the static data about the hierarchy. Furthermore, it is very easy to program search procedures, as Prolog uses depth rst search in the evaluation of programs. Prolog also allows for rapid and easy ....

Ivan Bratko. Prolog Programming for Arti cial Intelligence. Addison Wesley, second edition, 1990.

....value. This goal is Put= Selector,Output,Arg] called and the value is put Put. in the right place. After developing the class of Nodes, we can immediately start proving properties about it. For example, suppose we copy Input to Output except for the number which is set to the Prolog list [1,2,3], then we can prove in PVS that applying node copy(Input,number, 1,2,3] Output) implies that the formulas remain unchanged, but the number of Output is now [1,2,3] note that the list is represented in PVS by ( 1,2,3: node th1: THEOREM FORALL (node1,node2: NODES) ....

....is put Put. in the right place. After developing the class of Nodes, we can immediately start proving properties about it. For example, suppose we copy Input to Output except for the number which is set to the Prolog list [1,2,3] then we can prove in PVS that applying node copy(Input,number,[1,2,3],Output) implies that the formulas remain unchanged, but the number of Output is now [1,2,3] note that the list is represented in PVS by ( 1,2,3: node th1: THEOREM FORALL (node1,node2: NODES) node copy(node1,number, 1,2,3: node2) IMPLIES node formulas(node1) node formulas(node2) ....

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Bratko I., Prolog Programming for Articial Intelligence, Addison-Wesley, 2001.

....use (a subset of) rst order logic for representing the input as well as the learned rules, which makes such systems very exible. We will rst brie y introduce the Warmr system and then illustrate how it is used in our system. In this description we expect the user to be familiar with prolog (see [1] for more information on prolog) Warmr is a system which detects frequent patterns in relational data. It takes as input a set of observations, background knowledge and a language bias and searches for all legal patterns that are frequent in the set of observations. Each observation is written ....

I. Bratko. Prolog Programming for Articial Intelligence. Addison-Wesley, Wokingham, England, 1990. 2nd Edition.

....practice as exempli ed by the Prolog programming language. The theoretical portions are heavily based on [4] and a portion of this text is essentially a reordering of the material contained therein. The portions on Prolog and propositional logic are based on material from a variety of sources ([1], 6] 2] 5] Consider the following two statements: If the sun is shining then I wear sunglasses The sun is shining If both of these statements are true, then it is reasonable to conclude that I will be wearing sunglasses. This is an example of natural inference the conclusion I am ....

....insert(Head,L1,L) and the inserting is done by the following predicate insert(X, X] insert(X, Y Tail] Y L1] order(Y,X) insert(X,Tail,L1) insert(X, Y Tail] X,Y Tail] order(X,Y) 32 This sorting program sorts lists as expected, with one slightly strange feature. insort([4,1,3,1,7,2],L) L = 1,1,2,3,4,7] L = 1,1,2,3,4,7] no Prolog produced two solutions to the above query. The reason for this was that there are two 1s in the list, and therefore in the insert predicate there is a point when both of the clauses are satisi ed. In other words the two 1s get inserted in ....

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Bratko, I. PROLOG Programming for Articial Intelligence, Addison-Wesley, 1990.

....interpret Prolog code. There are two ways to avoid requiring the user to interpret Prolog code. The rst one is the Sternberg English solution. It basically consists of automatically translating the Prolog output into English using techniques one can nd in standard books on Prolog (such as e.g. [Bra90]) The other solution would be to represent the output hypotheses in some kind of relational data base language. However, at this point, not any database language will help. Indeed, it is unlikely that the typical domain expert will nd view de nitions in SQL or relational algebra more ....

I. Bratko. Prolog Programming for Articial Intelligence. AddisonWesley, 1990. 2nd Edition.

....and the previously used commands. Warmr doesn t automatically take into account these relations, but using background knowledge we can inform Warmr about these relations by de ning relations such as nextcommand and recentcommand. Background information is represented as Prolog programs, see (Bratko 1990) if you are unfamiliar with the used Prolog notation. nextcommand(CommandID,Nextcommand) NextID is CommandID 1 , command(NextID,Nextcommand) recentcommand(CommandID,Recentcommand) command(RecentCommandID,Recentcommand) Recentborder is RecentcommandID 5 , Recentborder CommandID ....

Bratko, I. 1990. Prolog Programming for Articial Intelligence. Addison-Wesley. 2nd Edition.

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Bratko, I. 1986.Prologprogramming for arti#cial intelligence. Addison-Wesley.

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I. Bratko. Prolog Programming for Arti cial Intelligence (2nd Edition). Addison Wesley, 1990.

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Bratko, I. Prolog: Programming for Arti cial Intelligence, Addison-Wesley, Singapore, pp. 302-329, 1993.

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Bratko, I., Prolog Programming for Arti cial Intelligence, Addison-Wesley, 1990.

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Ivan Bratko. Prolog Programming for Arti cial Intelligence. Addison-Wesley, Wokingham, 2nd edition, 1990.

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I. Bratko. Prolog Programming for Arti cial Intelligence. Addison-Wesley, 2001. 3rd Edition.

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I. Bratko. (1986). Prolog Programming for Articial Intelligence. International Computer Science. Addison-Wesley.

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