Dead Reckoning Using Play Patterns in a Simple 2D Multiplayer Online Game

In today’s gaming world, a player expects the same play experience whether playing on a local network or online with many geographically distant players on congested networks. Because of delay and loss, there may be discrepancies in the simulated environment from player to player, likely resulting in incorrect perception of events. It is desirable to develop methods that minimize this problem. Dead reckoning is one such method. Traditional dead reckoning schemes typically predict a player’s position linearly by assuming players move with constant force or velocity. In this paper, we consider team-based 2D online action games. In such games, player movement is rarely linear. Consequently, we implemented such a game to act as a test harness we used to collect a large amount of data from playing sessions involving a large number of experienced players. From analyzing this data, we identified play patterns, which we used to create three dead reckoning algorithms. We then used an extensive set of simulations to compare our algorithms with the IEEE standard dead reckoning algorithm and with the recent “Interest Scheme” algorithm. Our results are promising especially with respect to the average export error and the number of hits

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

Study and implementation of a real time online football game for mobile devices

The main goal of this project is extracting an optimized system to do a sensible application to delay loses and jitter in a wireless environment. This system will be used in a football game for mobile devices with maximum two players per game

An Information-Theoretic Framework for Consistency Maintenance in Distributed Interactive Applications

Distributed Interactive Applications (DIAs) enable geographically dispersed users to interact with each other in a virtual environment. A key factor to the success of a DIA is the maintenance of a consistent view of the shared virtual world for all the participants. However, maintaining consistent states in DIAs is difficult under real networks. State changes communicated by messages over such networks suffer latency leading to inconsistency across the application. Predictive Contract Mechanisms (PCMs) combat this problem through reducing the number of messages transmitted in return for perceptually tolerable inconsistency. This thesis examines the operation of PCMs using concepts and methods derived from information theory. This information theory perspective results in a novel information model of PCMs that quantifies and analyzes the efficiency of such methods in communicating the reduced state information, and a new adaptive multiple-model-based framework for improving consistency in DIAs. The first part of this thesis introduces information measurements of user behavior in DIAs and formalizes the information model for PCM operation. In presenting the information model, the statistical dependence in the entity state, which makes using extrapolation models to predict future user behavior possible, is evaluated. The efficiency of a PCM to exploit such predictability to reduce the amount of network resources required to maintain consistency is also investigated. It is demonstrated that from the information theory perspective, PCMs can be interpreted as a form of information reduction and compression. The second part of this thesis proposes an Information-Based Dynamic Extrapolation Model for dynamically selecting between extrapolation algorithms based on information evaluation and inferred network conditions. This model adapts PCM configurations to both user behavior and network conditions, and makes the most information-efficient use of the available network resources. In doing so, it improves PCM performance and consistency in DIAs

Toward Visualization for Games: Theory, Design Space, and Patterns

Abstract-Electronic games are starting to incorporate in-game telemetry that collects data about player, team, and community performance on a massive scale, and as data begins to accumulate, so does the demand for effectively analyzing this data. In this paper, we use examples from both old and new games of different genres to explore the theory and design space of visualization for games. Drawing on these examples, we define a design space for this novel research topic and use it to formulate design patterns for how to best apply visualization technology to games. We then discuss the implications that this new framework will potentially have on the design and development of game and visualization technology in the future

Dead Reckoning for Distributed Network Online Games

Online networked games are becoming increasingly popular. One type of network architecture used in these games is a distributed network architecture, where players send periodic updates to each other and each player must locally reconstruct the position of their opponents in between these updates. In this work, we assume a car model for the players, as errors in this type of network are most pronounced when players have high speeds. We are interested in decreasing this update frequency in order to conserve bandwidth. We are also interested in investigating issues that arise when these locally replicated opponents need to interact and collide with objects in the environment. In this thesis we decompose the replication problem into two components: first, we must predict the position of our opponents by extrapolating from the received updates, then we must create a smooth trajectory from these predicted positions that appears believable to the player. We introduce a neural network based approach to solving the prediction portion that outperforms the current state of the art. We then propose a neural network based approach and an approach based on a path tracking controller for mobile robots to generate smooth trajectories. We present results to compare these approaches and show that the path tracking approach performs better than both the neural network approach and the established state of the art approaches. We also investigate collisions between replicated opponents and the environment. This is a complex problem, so for simplicity we are only examining collisions with static obstacles. Collisions can vary dramatically based on small changes in impact point and angle, and so we want to be able to predict collisions based on the predicted position of the opponent because that is theoretically our best estimate of the true position of our opponent. We propose a neural network based approach to this problem, which is able to predict the collision response of a vehicle colliding with a static obstacle. We present results that show this method has potential to outperform the current best practice, but we also discuss several implementation issues that must be addressed

Approximation Algorithm for Estimating Distances in Distributed Virtual Environments

International audienceThis article deals with the issue of guaranteeing properties in Distributed Virtual Environments (DVEs) without a server and without global knowledge of the system state and therefore only by exchanging messages. This issue is particularly relevant in the case of online games, that operate in a fully distributed framework and for which network resources such as bandwidth are the critical resources. In the context of games, players typically need to know the distance between their character and other characters, at least approximately. Players all share the same position estimation algorithm but, in general, do not know the current positions of others. We provide a synchronized distributed algorithm Alc to guarantee, at any time, that the estimated distance d est between any pair of characters A and B is always a 1 + ε approximation of the current distance d act. Our result is twofold: (1) we prove that if characters move randomly on a d-dimensional grid, or follow a random continuous movement on up to three dimensions, the number of messages of Alc is optimal up to a constant factor; (2) in a more practical setting, we also observe that the number of messages of Alc for actual game traces is much less than the standard algorithm sending actual positions at a given frequency

Characterizing the Effects of Local Latency on Aim Performance in First Person Shooters

Real-time games such as first-person shooters (FPS) are sensitive to even small amounts of lag. The effects of network latency have been studied, but less is known about local latency -- that is, the lag caused by local sources such as input devices, displays, and the application. While local latency is important to gamers, we do not know how it affects aiming performance and whether we can reduce its negative effects. To explore these issues, we tested local latency in a variety of real-world gaming systems and carried out a controlled study focusing on targeting and tracking activities in an FPS game with varying degrees of local latency. In addition, we tested the ability of a lag compensation technique (based on aim assistance) to mitigate the negative effects. To motivate the need for these studies, we also examined how aim in FPS differs from pointing in standard 2D tasks, showing significant differences in performance metrics. Our studies found local latencies in the real-world range from 23 to 243~ms that cause significant and substantial degradation in performance (even for latencies as low as 41~ms). The studies also showed that our compensation technique worked well, reducing the problems caused by lag in the case of targeting, and removing the problem altogether in the case of tracking. Our work shows that local latency is a real and substantial problem -- but game developers can mitigate the problem with appropriate compensation methods