Intelligent Game Playing Using Neural Networks

Artificial Intelligence is the study of how to make computers do things which, at the moment, people do better. Game playing and Theorem proving share the property that people who do them well are considered to be displaying intelligence. Artificial Intelligence opens a new dimension of introducing intelligence inside machines.Initially the Computers could perform well at task such as playing games like Tic-Tac-Toe, where the numbers of solutions path are less. It was thought that this process required very less knowledge and could therefore be programmed easily. But even in simple games like Chess Playing there are around 10e100 possible moves for every move. So even to finish the first move would require our whole life time.
A neuron is a cell in the brain whose principal function is the collection, processing and dissemination of electrical signals. The brain’s information-processing capacity is thought to emerge primarily from networks of such neuron. For this some of the earliest AI work aimed to create artificial neural network. Researchers in AI and statistics became interested in the more abstract properties of neural networks. Such as their ability to perform distributed computation to tolerate noisy inputs, and to learn. Neural networks remain one of the most popular and effective forms of learning system.
Hence we use the concept of Neural Networks in game playing, making games more robust by inducing learning from experience ability. The BC3K Artificial Intelligence & Logistics, AILOG, engine, uses a neural net for very basic goal oriented decision making and route finding when navigating the vast expanse of the game's galaxy.
In this paper I explain the concept of game playing, different genres, role of neural networks hence AI and also the current research work going in the field of game playing and making games more intelligent.

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