Although mainly a research endeavor, the end goal of this project is to produce a system based on artificial neural networks (ANNs) which will play chess (as the dark side only) effectively against a human opponent. The dark side is chosen simply because it prevents the system from having to make the first move. To meet the objective, research will be centered on artificial neural network (ANN) topology, specifically for the purpose of creating a topology appropriate for complex problem solving. Functionality of the system may be broken into three parts; the learning mode will be a
In this work the author analyzes the usage of artificial neural networks in games. The author also a...
This report is about how a general-purpose neural network (LC0) operates compares to the domain-spec...
Most chess-playing programs are based on well known algorithms and determinisitc eval-uation functio...
The advancement of computing technology has allowed machines to defeat even the best human practitio...
Numerous published studies revealed that various researchers have attempted to build a program that ...
In this paper we propose a novel supervised learning approach for training Artificial Neural Network...
This thesis will cover the topic of artificial intelligence algorithms in the game of chess and thei...
This paper presents a neural network, based on Giraffe by Lai, that evaluates chess positions. It ...
En aquest treball es fa un estudi detallat de les Xarxes Neuronals, especialment de les xarxes neuro...
In artificial intelligence systems, various machine learning al-gorithms are used as learning algori...
Research in computer game playing has relied primarily on brute force searching approaches rather th...
This paper presents a neural network based methodology for examining the learning of game-playing ru...
The existence of endgame databases challenges us to extract higher-grade information and knowledge f...
We present a neural network methodology for learning game-playing rules in general. Existing researc...
We present a neural network methodology for learning game-playing rules in general. Existing researc...
In this work the author analyzes the usage of artificial neural networks in games. The author also a...
This report is about how a general-purpose neural network (LC0) operates compares to the domain-spec...
Most chess-playing programs are based on well known algorithms and determinisitc eval-uation functio...
The advancement of computing technology has allowed machines to defeat even the best human practitio...
Numerous published studies revealed that various researchers have attempted to build a program that ...
In this paper we propose a novel supervised learning approach for training Artificial Neural Network...
This thesis will cover the topic of artificial intelligence algorithms in the game of chess and thei...
This paper presents a neural network, based on Giraffe by Lai, that evaluates chess positions. It ...
En aquest treball es fa un estudi detallat de les Xarxes Neuronals, especialment de les xarxes neuro...
In artificial intelligence systems, various machine learning al-gorithms are used as learning algori...
Research in computer game playing has relied primarily on brute force searching approaches rather th...
This paper presents a neural network based methodology for examining the learning of game-playing ru...
The existence of endgame databases challenges us to extract higher-grade information and knowledge f...
We present a neural network methodology for learning game-playing rules in general. Existing researc...
We present a neural network methodology for learning game-playing rules in general. Existing researc...
In this work the author analyzes the usage of artificial neural networks in games. The author also a...
This report is about how a general-purpose neural network (LC0) operates compares to the domain-spec...
Most chess-playing programs are based on well known algorithms and determinisitc eval-uation functio...