Visual Logic Assignments 1-8 Flow Charts Taylor Atwood. Begin Output: name is Taylor Atwood' Output: 'l was born in Bossier City, Louisiana' Output: 'l enjoy spending time with. Visual Logic Free Download Jul 23, 2018 Babya Logic Pro.exe, ACAnwahl.exe and Babya ES10.exe are the most common filenames for this program's installer. This free software is. It looks like Visual Logic is windows only, so in order to run it on a mac you will need to either run windows on a virtual machine using a program like parallels. Using parallels you can run OS X and windows side by side without having to reboot.
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John R. Fisher
Luu Tran
10/12/95(2/2/96, last modified 6/20/96)© JRFisher
For illustration, consider the logic of the following paragraph. Theexample is hypothetical. It concerns certain assumptions regarding relevantfactors about guilt or innocence in a criminal trial. The example is supposedto compare various ways of presenting logical information, and to show someof the advantages of a visual approach.
First, we have a textual characterization of information.
The defendant is guilty provided that motive, opportunity,and incriminating forensic evidence can be established. Either jealousyand anger or else possessiveness and anger provide a motive and testimonyconfirms that the defendant was indeed angry, and either jealous or possessive. Opportunity can be established by showing that the defendant was nearby. There is evidence that the defendant was nearby during the crime. Opportunityis contravened by a reliable alibi, such as being observed somewhere elseat the time of the crime. The defendant has a witness to her being elsewhereat the time of the crime. Fingerprints are a conventional form or forensicevidence, and the defendant's fingerprints are present on the murder weapon.
Second, but without much explanation, we give a formal logic representationusing a typical kind of notation. Even if the reader has not specificallyseen this before, it should be possible to see connections between the following notations and the foregoing prose.
motive & opportunity & forensic_evidence -->guilty
anger & jealous --> motive
anger & possessive --> motive
anger
jealous or possessive
nearby --> opportunity
nearby
alibi --> ~ opportunity
observed_elsewhere --> alibi
observed_elsewhere
finger_prints_match --> forensic_evidence
finger_prints_match
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Third, consider the following graphical representation of the information. The connection with the second representation should be fairly clear.Figure 1
The display above resulted for a visual logic system used in an 'exploremode'. This mode explores the logical consequences of the data that it has. The answers are given in the form of trees showing visually how conclusionsare supported by the evidence. These question-answering facilities in theexplore mode are interactive. In the explore mode, the user might startby creating the top node for a query, and then make a choice for how toexpand a tree under the top node. Here is a graphical representation showinghow this looks for one of the current systems...
Figure 2
Figure 2 actually represents an earlier look at the tree in Figure 1,before it was completed to the 'true' leaves. The explore mode may allowmany choices to the user. In particular, nodes displayed in relief, if selected,may be 're-expanded' using other information, or rules of inference. Forexample, in Figure 1, the 'motive' node could be selected for re-expansionaccording to the other logical rule involving 'motive'. Selecting can bedone with the mouse or using arrow keys. Figures 3 and 4 show how thatwould look ...
Figure 3
Figure 4
The visual presentation of logical information can be enhanced usingcolor. In Figure 2, before conclusions have been verified, the nodes ofthe tree are displayed in some neutral color. In Figure 1, after conclusionshave actually been reached, the blue color represents conclusions that arein evidence. In Figure 4, after 'redoing' a node in Figure 3, some of thecolors return to neutral, indicating that potential further inferences needto be made. Different colors are used to represent different kinds of informationabout consequences, as subsequent examples will show.
The astute reader will have noticed that the logical data for the example has conflicts, or contradiction, in it. The conflict is actually quite apparent if one looks at the trees in the Figure 1, since the author choseto expand trees that expose the contradiction. The conclusion of 'guilt'is obviously not well supported, even though there is a kind of completedevidence in its favor. The problem is that 'opportunity' is conflicted,and the visual diagrams clearly show this. Perhaps the main advantage tothe visual approach is illustrated by this simple kind of example. A visuallogic system may or may not allow logical contradictions. If it does --and we have a system specifically designed to illuminate conflict -- then the visual logic must find a way to present the conflict in a revealingand decisive manner. In the 'query' mode of the current visual tool (beingdeveloped by Luu Tran) inference trees exposing logical conflict can begenerated automatically. Figure 5 shows this, using the current example ...
Figure 5
Figure 5 represents a screen snapshot in 'query' mode. The VL tool automatically queries the logical database to deduce 'evident' propositions (in blue onthe left). The user then clicks on a generated conclusion, and the toolshows the result of its search for support. In this case the reasoning enginehas deduced the conflict, which is shown in red in the diagram drawn on theright portion of the screen. If the user subsequently clicks on a red, orconflicted, node the tool will display the inference tree for its contrary(~opportunity in this case). This result is illustrated in Figure 6.
Figure 6
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The third reference provides a new mathematical theory for declarativeconflict upon which the current visual logic system is based. Even thoughthe theory is based upon concepts familiar to (exacting) intuition and (informed)common sense, the difficulty of the formal theory motivated the desire ofthe authors to explore some appropriate methods of visualization.
The theory and the visual tool (VL) both allow rules with logical variables. For example, consider the following set of rules, written in the actualinput form currently used ...
grandparent(X,Y) <- parent(X,Z), parent(Z,Y) .
parent(tom, alice) <- true .
parent(tom, bill) <- true .
parent(alice, jane) <- true .
parent(alice, john) <- true .
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Figure 7 explores some of the possibliities, produced by the visual tool...
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(b)
(c)
(d)
Figure 7
In (a), node 'grandparent(X,Y)' is expanded one level and the left childselected. In (b), the left child is expanded. Notice how variable bindingsare communicated to relevant parts of the tree. In (c), the right node selectedin (b) is expanded, producing an inference tree showing that grandparent(tom,jane) is evident. In (d) the selected node in (c) is 'redone' using otherinformation. Notice that this forces variable bindings so that the rightmostleaf 'parent(bill,Y)' cannot be satisfied, and this is indicated using thelight red coloring on the node.
The intention is to also make the visual logic tool adequate as an interactiveProlog debugging and visualization tool.
A visual logic system may also allow the user to enter the informationin a tree format, similar to formats previously displayed, using graphicaltools such as text boxes (user types in information) and line drawing tools. This is a form of visual programming: The visual logic system builds aninternal representation for this information that is sufficient for furtherlogical analysis. In the graphical input, related information need notall be connected together to form larger trees, as was done in this simpleexample, but could be given by the user in a piecemeal fashion -- say, onerule at a time.
References
[1] Fisher, John R., Semantic trees for disjunctive logic programs, Proc.Third Golden West International Conference, ed. E.A. Yfantis, KluwerAcademic Publishers, 1995, pp. 291-305.
[2] Fisher, John R., Tree-based semantics for logic programs with negation as failure, The Journal of Interdisciplinary Studies, CaliforniaState Polytechnic University, Fall 1994, pp. 107-116.
[3] Fisher, John R, and Tran, Luu, A visual logic, Proc. 1996 ACMSymposium on Applied Computing (SAC96), Philadelphia, Penn., pp. 17-21.
[4] Tran, Luu, Visual Logic, A Visual Logic, MastersThesis, California State Polytechnic University, 1996.
[2] Fisher, John R., Tree-based semantics for logic programs with negation as failure, The Journal of Interdisciplinary Studies, CaliforniaState Polytechnic University, Fall 1994, pp. 107-116.
[3] Fisher, John R, and Tran, Luu, A visual logic, Proc. 1996 ACMSymposium on Applied Computing (SAC96), Philadelphia, Penn., pp. 17-21.
[4] Tran, Luu, Visual Logic, A Visual Logic, MastersThesis, California State Polytechnic University, 1996.