Ever since the first machines were made the man is trying to develop AI or Artificial Intelligence in machines so that they work independently and take decisions on their own without any help.
Now Mikhail Rabinovich and his colleague at the Institute for Nonlinear Science at the University of California have purposed a new break away theory called Sequential decision making. They are also being helped by Valentin Afraimovich of Institute for the Investigation of Optical Communication at the University of San Luis Potosi in Mexico in their research.
As Mikhail puts it ‘Decision making is everywhere, and not just with humans. Animals use it, and robots do. But the traditional approach to decision making is too simple.
But in real life the living being has to take lots of decisions in which many factors like environment, physical condition, and the state of mind effect the process of decision making. So far in Robots the decisions are made by the supervisor or the controller even if it is to decide whether to go left or right. They recently published their paper titled ‘Dynamics of Sequential Decision Making‘.
Earlier and up till now there is a simple if- then statement and does not consider other probabilities. The decisions in the real life are much more than a simple If-then equation and are much more depended on Sequential Decision making capabilities.
It is here that this new search might come in help as they are purposing a approach which takes into consideration all the dynamics and probabilities.
Rabinovich explains it with an example of a hunter and hunted a hunter has to make decision at every point of chase, at every turn of its prey and similarly prey also has to make real life decisions during the chase depending upon the terrain and the environment if it has to live. Same is the case if we have to develop a functional AI in robots so that they can make decisions like speed or were to go depending upon the environment and needs.
