Centralized Versus Decentralized Team Coordination Using Dynamic Scripting

Computer generated forces (CGFs) must display realistic behavior for tactical training simulations to yield an effective training experience. Tradionally, the behavior of CGFs is scripted. However, there are three drawbacks, viz. (1) scripting limits the adaptive behavior of CGFs, (2) creating scripts is difficult and (3) it requires scarce domain expertise. A promising machine learning technique is the dynamic scripting of CGF behavior. In simulating air combat scenarios, team behavior is important, both with and without communication. While dynamic scripting has been reported to be effective in creating behavior for single fighters, it has not often been used for team coordination. The dynamic scripting technique is sufficiently flexible to be used for different team coordination methods. In this paper, we report the first results on centralized coordination of dynamically scripted air combat teams, and compare these results to a decentralized approach from earlier work. We find that using the centralized approach leads to higher performance and more efficient learning, although creativity of the solutions seems bounded by the reduced complexity

Past Our Prime:A Study of Age & Play Style Development in Battlefield 3

In recent decades video games have come to appeal to people of all ages. The effect of age on how people play games is not fully understood. In this paper we delve into the question how age relates to an individual’s play style. ‘Play style’ is defined as any (set of) patterns in game actions performed by a player. Based on data from 10,416 Battlefield 3 players, we found that age strongly correlates to how people start out playing a game (initial play style), and to how they change their play style over time (play style development). Our data shows three major trends: (1) correlations between age and initial play style peak around the age of 20; (2) performance decreases with age; and (3) speed of play decreases with age. The relationship between age and play style may be explained by the neuro-cognitive effects of aging: as people grow older, their cognitive performance decays, their personalities shift to a more conscientious style, and their gaming motivations become less achievement-oriented

Improving multivariate Horner schemes with Monte Carlo tree search

Optimizing the cost of evaluating a polynomial is a classic problem in computer science. For polynomials in one variable, Horner's method provides a scheme for producing a computationally efficient form. For multivariate polynomials it is possible to generalize Horner's method, but this leaves freedom in the order of the variables. Traditionally, greedy schemes like most-occurring variable first are used. This simple textbook algorithm has given remarkably efficient results. Finding better algorithms has proved difficult. In trying to improve upon the greedy scheme we have implemented Monte Carlo tree search, a recent search method from the field of artificial intelligence. This results in better Horner schemes and reduces the cost of evaluating polynomials, sometimes by factors up to two.Comment: 5 page

What Can Be Learned From a Knowledge-intensive System?

The paper aims at describing what can be learned from a Knowledge-intensive Sys-tem (KIS) by a manager of an Indonesian SME Garment Manufacturer (ISGM).For this purpose, we use the system LIA (Leading to Information Access). LIA isa system that (1) handles financial related transactions, (2) processes them accordingto Indonesian accounting standard procedures, and (3) gives the interpretation of theprocess results to the financial analysis. By learning from the interpretation of thecompany's historical data, an owner's understanding of critical financial factors ingarment industry may increase and let the company flourish

What can be learned from a Knowledge-intensive System?

The paper aims at describing what can be learned from a Knowledge-intensive Sys-tem (KIS) by a manager of an Indonesian SME Garment Manufacturer (ISGM).For this purpose, we use the system LIA (Leading to Information Access). LIA isa system that (1) handles financial related transactions, (2) processes them accordingto Indonesian accounting standard procedures, and (3) gives the interpretation of theprocess results to the financial analysis. By learning from the interpretation of thecompany’s historical data, an owner’s understanding of critical financial factors ingarment industry may increase and let the company flourish.Keywords: Knowledge-intensive System, Financial Analysis, Learning Process,Indonesia SME Garment Manufacturers, Business Administratio

The Design and Evaluation of a Knowledge-intensive System

AbstractTo make an appropriate decision, a manager needs to be supported with qualified information and adequate knowledge in interpreting the information. A challenging situation arises when the manager has only limited time for formulating an appropriate decision. One of the solutions is to support the manager with a Knowledge-intensive System (KIS). The paper presents the findings of an evaluation of a KIS called Leading to Information Access (LIA). There are four principal components in the evaluation of LIA, namely (1) an acceptable satisfaction level in using LIA, (2) good assessment of LIA s performance, (3) an acceptable level of computer literacy, and (4) a high confidence of LIA s usefulness