A team of researchers in the United States has developed a new computing model that allows artificial intelligence systems to make better decisions by enhancing their ability to deal with ambiguities. This model allows artificial intelligence systems to make better choices, which enhances their ability in certain areas that require making critical decisions and during limited periods of time, such as self-driving car steering systems.

Artificial intelligence systems are forced to deal with many factors and ambiguous circumstances for them, which often result from human behaviors, and in order to reduce these ambiguous elements, artificial intelligence systems use intensive mathematical operations to analyze the different situations and the results related to them, then they turn towards The best options.

They added that the new technology reached by a research team from the University of California and Austin in the USA brings many improvements to the decision-making mechanisms of smart systems, and results in better, faster and safer results. The study team says that the new development comes thanks to the reliance on a new way of thinking about ambiguous matters known as the “Markov decision-making process by partial observation”. This method is based on evaluating the potential consequences of any decision.

Researcher Ahmed Reda Marandi confirms that the new system can make very important decisions within a very short period of time, depending on a large amount of available data, and can be used in many areas in practical life, such as predicting the size of a specific virus, or protecting endangered species, as well as directing Aircraft and spacecraft to avoid the possibility of accidents.