Contextual High-Level Uncertainty Modeling Reducing Surprises in Decision Making

In life of animals and humans, there are different stages where uncertainty plays a key role. These uncertainties create risks and surprises which will certainly impact decision making. In ideal scenario, pattern-based or rule-based systems will surely work, as Decision making is completely dependent on known and predictive inputs from environments as well as intelligent agents. But when it comes to high level decision making, these surprises bring down the accuracy. To identify precisely and model such uncertainty correctly is a challenge. There are different techniques used by researchers like fuzzy logic based, probability theory based and many more to model uncertainty. This paper illustrates these techniques with a new model proposed to learn from the uncertainty for decision making.