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Decision making with Uncertainty in Artificial Intelligence

In this article, we are going to learn about how the decision-making process is performed inside an expert system or any AI based agent when there are certain uncertainties present in the conditions faced by the system/agent? We will study the various types by which the agent makes the decisions.
Submitted by Monika Sharma, on June 11, 2019

When the conditions are not certain for a computer system or an Artificially Intelligent agent, then there needs to be a method through which the agent can take decisions in uncertain situations also. For this, many methods were proposed by different developers and computer professionals. The following three are among the basic and widely used methods to perform decision making while handling the uncertainty:

  1. Probabilistic Theory
  2. Fuzzy Logic
  3. Truth Maintenance

1) Probability Theory

The main reason for proposing this theory for reasoning was that there are situations where we cannot decide whether our statement or event is completely true or completely false. In most of the cases, the conditions appear to be partially true. So, this representation was not possible in the Boolean knowledge representation. So, to overcome this problem, the Probabilistic theory was introduced in which we can determine how likely an event is to happen. This estimation is done by assigning a real number within the range 0 to 1 where 0 represents that the event will never occur during the whole experiment, whereas 1 represents that whenever the experiment will be performed, that event will surely take place.

2) Fuzzy Logic

Fuzzy Logic is also somewhat similar to Probability theory. The difference is that, in fuzzy logic, the agent is trained to imitate the reasoning process of humans. Fuzzy Logic is termed better than Probabilistic theory in Artificial Intelligence because it emphasizes the system to think, analyze and act humanely. In fuzzy logic also, all the possible values between the range 0 to 1 are considered and the system produces a real number lying between this range which determines the possibility of the event.

3) Truth Maintenance

The Truth Maintenance process of decision making works on the basic logic that the knowledge that a system considers valid till now can become invalid in the situations which may arise in the future. This system is very useful to deal with the real world that it solves the most basic problem of uncertainty, which is the dynamic environment. As the system's surroundings keep changing as the time passes, the Truth Maintenance System keeps a record of the data which is valid till now. The data which becomes invalid is either moved to trash or is stored in some other file. The reason behind storing this data in some other file is that there may occur situations in the future where this data can again turn out to be valid.






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