A Multi-Agent Approach to the Game of Go Using Genetic Algorithms

This is the published version. Copyright De GruyterMany researchers have written or attempted to write programs that play the ancient Chinese board game called Go. Although some programs play the game quite well compared with beginners, few play extremely well, and none of the best programs rely on soft computing artificial intelligence techniques like genetic algorithms or neural networks. This paper explores the advantages and possibilities of using genetic algorithms to evolve a multiagent Go player. We show that although individual agents may play poorly, collectively the agents working together play the game significantly better

Implementation of an Intelligent Force Feedback Multimedia Game

This is the published version. Copyright De GruyterThis paper presents the design and programming of an intelligent multimedia computer game, enhanced with force feedback. The augmentation of game images and sounds with appropriate force feedback improves the quality of the game, making it more interesting and more interactive. We used the Immersion Corporation's force feedback joystick, the I-FORCE Studio computation engine, and the Microsoft DirectX Software Development Kit (SDK) to design the multimedia game, running in the Windows NT operating system. In this game, the world contains circles of different sizes and masses. When the circles hit each other, collisions take place, which are shown to, and felt by, the user. When the circles hit together, the overall score increases; the larger the size of the circle, the higher the score increase. The initial score is set to zero, and when the game ends, a lower score represents a better performance. This game was used to examine the behavior of the users under different environments through their respective scores and comments. The analysis of experimental results helps in the comparative study of different kinds of multimedia combinations

Plan and Intent Recognition in a Multi-agent System for Collective Box Pushing

This is the published version.In a distributed multi-agent system, an idle agent may be available to assist other agents in the system. An agent architecture called intent recognition is proposed in this article to accomplish this with minimal communication. To assist other agents in the system, an agent performing recognition observes the tasks other agents are performing. Unlike the much-studied field of plan recognition, the overall intent of an agent is recognized instead of a specific plan. The observing agent may use capabilities that it has not observed. In this study, the key research question is: What are intent-recognition systems and how can these be used to have agents autonomously assist each other effectively and efficiently? A conceptual framework is proposed to address this question. An implementation of the conceptual framework is tested and evaluated. A set of metrics, including task time and number of communications, is used to compare the performance of plan recognition and intent recognition. This research shows that under certain conditions, an intent-recognition system is more efficient than a plan recognition system

Currency Exchange Rate Forecasting with Neural Networks

This is the published version. Copyright De GruyterThis paper presents the prediction of foreign currency exchange rates using artificial neural networks. Since neural networks can generalize from past experience, they represent a significant advancement over traditional trading systems, which require a knowledgeable expert to define trading rules to represent market dynamics. It is practically impossible to expect that one expert can devise trading rules that account for, and accurately reflect, volatile and rapidly changing market conditions. With neural networks, a trader may use the predictive information alone or with other available analytical tools to fit the trading style, risk propensity, and capitalization. Numerous factors affect the foreign exchange market, as they will be described in this paper. The neural network will help minimize these factors by simply giving an estimated exchange rate for a future day (given its previous knowledge gained from extensive training). Because the field of financial forecasting is too large, the scope in this paper is narrowed to the foreign exchange market, specifically the value of the Japanese Yen against the United States Dollar, two of the most important currencies in the foreign exchange market

A Novel Efficient Algorithm for Locating and Tracking Object Parts in Low Resolution Videos

This is the published version. Copyright De GruyterIn this paper, a novel efficient algorithm is presented for locating and tracking object parts in low resolution videos using Lowe's SIFT keypoints with a nearest neighbor object detection approach. Our interest lies in using this information as one step in the process of automatically programming service, household, or personal robots to perform the skills that are being taught in easily obtainable instructional videos. In the reported experiments, the system looked for 14 parts of inanimate and animate objects in 40 natural outdoor scenes. The scenes were frames from a low-resolution instructional video on cleaning golf clubs containing 2,405 frames of 180 by 240 pixels. The system was trained using 39 frames that were half-way between the test frames. Despite the low resolution quality of the instructional video and occluded training samples, the system achieved a recall of 49 % with a precision of 71 % and an Fl of 0.58, which is better than that achieved by less demanding applications. In order to verify that the reported results were not dependent on the specific video, the proposed technique was applied to another video and the results are reported

Modeling Firewalls for Behavior Analysis

AbstractThis work presents a software behavioral model of the capabilities found in firewall type devices and a process for taking vendor specific nuances to a common implementation. This includes understanding interfaces, routes, rules, translation, and policies; modeling them in a common manner such that different models may be compared to each other for functional similarity. This work makes use of recent efforts to model firewall policies in a concise efficient data structure referred to as a Firewall Policy Diagram (FPD). The structure facilitates the canonical representation of a policy as well as human comprehension of the policy. Its use with behavior modeling is to capture and compare the results of a potentially large solution space

Data Mining and Hypothesis Refinement Using a Multi-Tiered Genetic Algorithm

This is the published version. Copyright De GruyterThis paper details a novel data mining technique that combines set objects with an enhanced genetic algorithm. By performing direct manipulation of sets, the encoding process used in genetic algorithms can be eliminated. The sets are used, manipulated, mutated, and combined, until a solution is reached. The contributions of this paper are two-fold: the development of a multi-tiered genetic algorithm technique, and its ability to perform not only data mining but also hypothesis refinement. The multi-tiered genetic algorithm is not only a closer approximation to genetics in the natural world, but also a method for combining the two main approaches for genetic algorithms in data mining, namely, the Pittsburg and Michigan approaches. These approaches were combined, and implemented. The experimental results showed that the developed system can be a successful data mining tool. More important, testing the hypothesis refinement capability of this approach illustrated that it could take a data model generated by some other technique and improves upon the overall performance of the data model

Multi-Agent Task Allocation for Robot Soccer

This is the published version. Copyright De GruyterThis paper models and analyzes task allocation methodologies for multiagent systems. The evaluation process was implemented as a collection of simulated soccer matches. A soccer-simulation software package was used as the test-bed as it provided the necessary features for implementing and testing the methodologies. The methodologies were tested through competitions with a number of available soccer strategies. Soccer game scores, communication, robustness, fault-tolerance, and replanning capabilities were the parameters used as the evaluation criteria for the mul1i-agent systems

Design and Simulation of a Polar Mobile Robot

This is the published version. Copyright De GruyterThis paper describes the design and simulation of a mobile robot for missions in polar regions. The robot was designed to provide mobility, power, precise positioning and environmental protection for a bistatic synthetic aperture radar for polar regions to measure ice thickness and other ice sheet characteristics. The robot is required to carry and protect the radar system and to tow a large antenna, while providing precise positioning of the antenna to the accuracy of within a few centimeters. In parallel to the design and fabrication of an actual robot, a simulation model of the robot was designed and a virtual prototype was built to perform numerous experiments without the need for actual deployment in polar regions. These experiments tested robot characteristics such as slopes in the terrain, rolling effects, turning radii, antenna attachments, and payload distribution

An Emotion Theory Approach to Artificial Emotion Systems for Robots and Intelligent Systems: Survey and Classification

This is the published version.To assist in the evaluation process when determining architectures for new robots and intelligent systems equipped with artificial emotions, it is beneficial to understand the systems that have been built previously. Other surveys have classified these systems on the basis of their technological features. In this survey paper, we present a classification system based on a model similar to that used in psychology and philosophy for theories of emotion. This makes possible a connection to thousands of years of discourse on the topic of emotion. Five theories of emotion are described based on an emotion theory model proposed by Power and Dalgleish. The paper provides classifications using a model of 10 new questions, for 14 major research projects that describe implementations or designs for systems that use artificial emotions for either robotics or general artificial intelligenc