Nt1310 Unit 3 Problem Analysis Paper

AI in the gaming world is common and widely used in our daily life. When playing against the computer, AI becomes involved by assisting with determining what moves to make (Mike Fekety 2015). One good thing about AI or computer is that it does not require sleep or breaks. Like the energizer bunny, it keeps on going and going without stopping (Rounak, 2017).

Artificial Intelligence is the taking over of machines to do tasks that would normally require a human to do. The idea of artificial intelligence has been around for years, appearing in movies and television shows to show what the future might bring. Artificial intelligence is becoming closer to a reality and now society must question if it should have a role in society. Artificial intelligence has many flaws at the moment making it impractical for use until society can address the issues facing it like the loss of jobs and how to control the use of AI.

I believe that AI will be a key feature in next generation video games, especially in Virtual Reality (VR) systems. As AI advances, I am sure the realism in VR

The objective of the neural network is to transform the input to meaningful output. Neural networks are often used for statistical analysis and data modeling. Neural network has many uses in data processing, robotics, and medical diagnosis [2]. From the starting of the neural network there are various types found, but each and every types has some advantages and disadvantages. Deep learning and -neural network software are the categories of artificial neural network. The parallel process also allows ANNs to process the large amount of data very efficiently. The artificial neural network is built with a systematic

Artificial intelligence is the development of a computer system that is able to perform tasks of human intelligence like visual perception, speech recognition, and decision-making. Computer scientists have made a substantial advancement in the

Neural Network The idea envisaged for the neural network was that of a feed-forward neural network with a hidden layer. This was due to experience and familiarity with them from the Part IB ’Artificial Intelligence’ course. It was necessary to research neural network frameworks in order to

Two months ago Open AI’s artificial intelligence beat the world’s best Dota 2 player in a one versus one battle. Unlike chess or go, Dota 2 doesn't have any simple rules that can be converted into algorithms for the AI. Instead it was merely given the controls, a goal, and time. It learned how to play just from two weeks of failures against itself until it was better than every human. This is the first complex, non algorithmic victory for AI and it is slightly terrifying because it means they can learn tasks more complicated than simple logic based rules, such as dealing with unpredictability on the jobsite or human error. AI is becoming so developed it is only a matter of time before it fully integrates into our society. But we are not

More accuracy can be achieved by refining our data and knowing the significance of different attributes in the data, or the role of training or transfer functions. The role of neural networks and its working is still a mystery and is gradually evolution

Your thoughts on other aspects of Game theory that can be applied for this problem

The main task of the paper is to understand how strategic interactions in sports are applied, especially how players behave during games.

Each learing or training methods in supervised learing depends on the idea display data training in front of the network in the form of a pair of forms input form and target form. (See Figure (2-5)) .

The field of artificial intelligence gained in popularity during the twentieth century, accompanying the rise in ubiquity of computers. During this time, the main goal of research was to use computers to solve problems in an intelligent manner. In other words, researchers sought to develop algorithms that learn how to solve problems. Quinlan mentions that one group of researchers focused on creating programs that learn through a feedback cycle of self-testing and “adjusting internal parameters.” A good example of this would be a program written to play checkers against itself many thousands of times. Each time a sequences of moves produces a winning result, that sequence is given a

Each player knows that his or her opponent is also making the best possible moves

To cater the need of computer animation, interactive media such as games and virtual reality there is need for intelligent agent, those who can navigate according to requirement. These agents may have some ability to improvise their actions according to situation. This project will use the term intelligent to denote these agents which are intelligent agents in a virtual world who may be interacting with other agents. Intelligent agents are intended for use in computer animation and various interactive media such as games and virtual reality. This project will use the term virtual to denote these agents which, rather than being simulations of an electrical device in the real world, are instead intelligent agents in a virtual world.

Multiple-layer neural network using back propagation training algorithm is popular in neural network modeling because of its ability to recognize the pattern and relationship between non-linear signals. The term of back propagation usually refers to the manner in which the gradients of weights are computed for non-linear multi-layer networks. A neural network must be trained to determine the values of the weights that will produce the correct outputs. The standard or basic training method is called 'Gradient Descent Method’; in which weight changes move the weights in the direction where the error declines most quickly.