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This paper demonstrates the difference in rules and their impact in procedural generation of item in role-playing game. The main aims of this project are to: create a wave challenge-based game prototype that generates 2 items using the two rule-based randomized algorithms per wave, and identify the reasons in rules that affect the user's preference of item. Experimental results demonstrate success...
Business and financial news bring us the latest information about the stock market. Studies have shown that business and financial news have a strong correlation with future stock performance. Therefore, extracting sentiments and opinions from business and financial news is useful as it may assist in the stock price predictions. In this paper, we present a sentiment analyser for financial news articles...
This paper describes the performance of four crossover operators used in evolving the required controllers in a video game. The crossover operators used in this research are the two-point crossover, the uniform crossover, the N-point crossover, and the single-point crossover. The performance of these crossover methods were tested using Infinite Mario Bros game. This video game was chosen due to the...
Stock market is a promising financial investment that can generate great wealth. However, the volatile nature of the stock market makes it a very high risk investment. Thus, a lot of researchers have contributed their efforts to forecast the stock market pricing and average movement. Researchers have used various methods in computer science and economics in their quests to gain a piece of this volatile...
In this paper, we describe the results of implementing Genetic Programming (GP) using two different Artificial Neural Networks (ANN) topologies in a customized Tower Defense (TD) games. The ANNs used are (1) Feed-forward Neural Network (FFNN) and (2) Elman-Recurrent Neural Network (ERNN). TD game is one of the strategy game genres. Players are required to build towers in order to prevent the creeps...
Spell checker is a system that is used to detect and correct misspelled word. Misspelled word is a word that exists in the existing lexicon that is not correctly spelled or in shortened form. These misspelled words often result in ineffective results of the Information Retrieval (IR) application such as document retrieval. This is because IR application should be able to recognize all words in a particular...
As the number of research papers increases, the need for academic categorizer system becomes crucial. This is to help academicians organize their research papers into pre-defined categories based on the documents' content similarity. This paper presents the Document Categorizer Agent based on ACM CCS (Association for Computing Machinery Computing Classification System). First, we studied the ACM categories...
This paper presents the design and evaluation of a full AI controller for Real-Time Strategy (RTS) games using techniques from Evolutionary Computing (EC). The design is novel in its use of a modified Pareto Differential Evolution (PDE) algorithm for bi-objective optimization of the weights of an Artificial Neural Network (ANN) controller when only single-objective optimization has so far been studied...
This paper demonstrates the research results obtained for the application of Differential Evolution (DE) algorithm in a well known real time strategy game, namely Warcraft 3. The DE algorithm is one of the global optimizers that commonly used in solving real-time problems. In this work, the DE algorithm is combined with the conventional feed-forward artificial neural network in optimizing the solutions...
In this paper we present the possibilities of implementing evolution algorithm on a mobile platform. To inspect such possibilities we have created a Pac-man like mobile game that is implemented together with evolutionary programming. Here the interest does not only lie on performing the evolution algorithm on the mobile platform but also to examine the possibilities in implementing interactive evolution...
Evolutionary Algorithm (EA) is commonly used to generate optimal Artificial Intelligence (AI) controller. It is a technique used to enhance the performance of generated controller. EA enables the system to evolve, to adapt and learn to give a better output. The implementation of EA into 2D game is not something new. Researchers used gaming platforms to test their own ideology or proposed algorithms...
This paper presents the research results found for the utilization of a Genetic Algorithm (GA) technique in evolving a set of Artificial Neural Networks (ANNs) weights which functions as controller in deciding what type of unit that should be spawned for winning against the opponent in a RTS game called War craft 3 (custom map). The elitism concept is applied during the optimization processes in order...
The implementation of Artificial Intelligence (AI)in 3-Dimensional (3D) First Person Shooter (FPS) game is quite general nowadays. Most of the conventional AI bots created are mostly from hard coded AI bots. Hence, it has limited the dynamicity of the AI bots and therefore it brings to a fixed strategy for gaming. The main focus of this paper is to discuss the methodologies used in generating the...
In this paper, we investigate the utilization of a multi-objective approach for evolving artificial neural networks (ANNs) that act as controllers for a radio frequency (RF) based collective box-pushing task of a group of virtual E-puck robots simulated in a 3D, physics-based environment. The modified Pareto-frontier Differential Evolution (PDE) algorithm is used to generate the Pareto optimal sets...
The proliferation of online auctions has caused the increasing need to monitor and track multiple bids in multiple auctions. An autonomous agent was developed to work in a flexible and configurable heuristic decision making framework that can tackle the problem of bidding across multiple auctions that apply different protocols (English, Vickrey and Dutch) as a solution to the problem. This agent utilizes...
This paper discussed the utilization of a multi-objective approach for evolving artificial neural networks (ANNs) that act as a controller for radio frequency (RF)-localization behavior of a virtual Khepera robot simulated in a 3D, physics-based environment. The Pareto-frontier Differential Evolution (PDE) algorithm is used to generate the Pareto optimal sets of ANNs that optimize the conflicting...
Little work has been done on using the evolutionary multi-objective approach in evolving the robot controllers. In this study, a multi-objective approach is utilized in evolving the artificial neural networks (ANNs) for autonomous mobile robot controller. The neural network acts as a controller for radio frequency (RF)-localization behavior of a Khepera robot simulated in a 3D physics-based environment...
Many have treated mutation operators as a supplement operator in genetic algorithm. Researches have shown that the mutation operator plays an important role in genetic algorithm. This paper investigates the influences of the variation of mutation rate in genetic algorithms when applied to bidding strategies in online auctions. The proposed bidding strategy is polynomial in nature in which it will...
In this study, we investigate the utilization of a multi-objective approach in evolving artificial neural networks (ANNs) for an autonomous mobile robot. The ANN acts as a controller for radio frequency (RF)-localization behavior of a Khepera robot simulated in a 3D physics-based environment. The elitist Pareto-frontier Differential Evolution (PDE) algorithm is used to generate the Pareto optimal...
This paper investigates the utilization of a multi- objective approach for evolving artificial neural networks (ANNs) that act as a controller for radio frequency (RF)- localization behavior of a virtual Khepera robot simulated in a 3D, physics-based environment. The non-elitist and elitist Pareto-frontier Differential Evolution (PDE) algorithm are used to generate the Pareto optimal sets of ANNs...
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