Decision tables (or logic tables) and decision trees (or decision diagrams) describe the conditions associated with particular actions or decisions, together with the relevant constraints. Decision tables depict decision rules as rows and conditions as columns, with each cell representing the required action. Decision trees show conditions and actions in a sequence (like a flow chart); decision points are represented as diamonds and actions as boxes (Gottesdiener, 2002).
Decision tables and decision trees are useful when you want to address questions such as "what conditions influence various decisions?" or "what is the order in which the decision maker will check the conditions?" (Gottesdiener, 2002). Programmers frequently use decision tables because they translate directly into programmable logic (Goldsmith, 2004).
The two forms of representation are equivalent representations of decision problems. Any decision that can be depicted in a decision table format can also be represented by a decision tree and vice versa (French, 1989).
The idea underlying a tabular representation of a decision problem is that the consequence of any decision is influenced not just by the action but also by external factors. External factors are not controlled by the decision maker and are unknown to her at the time of decision making. These external factors are referred to as "the state of nature" or "the state." In other words, the action of the decision maker combined with the state of nature leads to consequences (French, 1989).
Decision trees force the programmer, system analyst or the decision maker to identify the actual decision that must be taken into consideration. They also help the decision maker follow the sequence of decision. In certain circumstances, decision tables are preferred because they are easier to draw, represent information in compact form and are easier to understand and modify (Dixit and Dixit, 2005).
Information presented in the decision tree format does not represent what other combinations of conditions can be tested in addition to the given set. A decision table can be more useful in such cases. A decision tree becomes unwieldy when the problem is complex and many sequences of steps are involved (Dixit and Dixit, 2005). The disadvantages of decision tables are: the burden of preparing them, no depiction of the flow of decision and inability to depict all alternatives (Agarwal et al., 2009).
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