Agent Based Modeling in Computer Graphics and Games

As graphics technology has improved in recent years, more and more importance has been placed on the behavior of virtual characters in applications set in virtual worlds in areas such as games, movies and simulations. The behavior of virtual characters should be believable in order to create the illusion that these virtual worlds are populated with living characters. This has led to the application of agent-based modeling to the control of these virtual characters. There are a number of advantages of using agent-based modeling techniques which include the fact that they remove the requirement for hand controlling all agents in a virtual environment, and allow agents in games to respond to unexpected actions by players

An Emotion Model for Video Game AI

Modeling human behavior in computer simulations and games is a subject which draws considerable attention. Despite the increased realism of graphics in games, poor modeling of non-player characters AI often leads to a shallow and unfulfilling game experience. Recently there has been increased focus on more sophisticated AI routines which have been used in both academic and commercial games. Emotion, however, is often ignored despite being an essential element of human behavior especially under stressful conditions. Research into the use of emotion in agent-based systems seems more concerned with how to convey the emotions of agents to the human player, or how to elicit an emotional response from the human player. Only recently has there been research on modeling emotions in combat simulators. This thesis will describe an emotional model suitable for most computer games which was adapted from the DETT model and significantly expanded\u2

Simulation-based visual analysis of individual and group dynamic behavior

The article presents a new framework for individual and group dynamic behavior analysis with wide applicability to video surveillance and security, accidents and safety management, customer insight and computer games. It combines graphical multi-agent simulation and motion pattern recognition for performing visual data analysis using an object-centric approach. The article describes the simulation model used for modeling the individual and group dynamics which is based on the analytical description of dynamic trajectories in closed micro-worlds and the individual and group behavior patterns exhibited by the agents in the visual scene. The simulator is implemented using 3D graphics tools and supports real-time event log analysis for pattern recognition and classification of the individual and group agent’s behavior

Overview of crowd simulation in computer graphics

High-powered technology use computer graphics in education, entertainment, games, simulation, and virtual heritage applications has led it to become an important area of research. In simulation, according to Tecchia et al. (2002), it is important to create an interactive, complex, and realistic virtual world so that the user can have an immersive experience during navigation through the world. As the size and complexity of the environments in the virtual world increased, it becomes more necessary to populate them with peoples, and this is the reason why rendering the crowd in real-time is very crucial. Generally, crowd simulation consists of three important areas. They are realism of behavioral (Thompson and Marchant 1995), high-quality visualization (Dobbyn et al. 2005) and convergence of both areas. Realism of behavioral is mainly used for simple 2D visualizations because most of the attentions are concentrated on simulating the behaviors of the group. High quality visualization is regularly used for movie productions and computer games. It gives intention on producing more convincing visual rather than realism of behaviors. The convergences of both areas are mainly used for application like training systems. In order to make the training system more effective, the element of valid replication of the behaviors and high-quality visualization is added

A survey of real-time crowd rendering

In this survey we review, classify and compare existing approaches for real-time crowd rendering. We first overview character animation techniques, as they are highly tied to crowd rendering performance, and then we analyze the state of the art in crowd rendering. We discuss different representations for level-of-detail (LoD) rendering of animated characters, including polygon-based, point-based, and image-based techniques, and review different criteria for runtime LoD selection. Besides LoD approaches, we review classic acceleration schemes, such as frustum culling and occlusion culling, and describe how they can be adapted to handle crowds of animated characters. We also discuss specific acceleration techniques for crowd rendering, such as primitive pseudo-instancing, palette skinning, and dynamic key-pose caching, which benefit from current graphics hardware. We also address other factors affecting performance and realism of crowds such as lighting, shadowing, clothing and variability. Finally we provide an exhaustive comparison of the most relevant approaches in the field.Peer ReviewedPostprint (author's final draft

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion