The Use of Computer Games for Promotional Purposes

This study is focused on computer game series Needfor Speed （NFS） in terms of its use in promotion of products and brands. We believe that computer games are no longer the domain of a small group of enthusiasts. In recent years, this kind of entertainment has became a global phenomenon, which is reflected both on professional and scientific levels. This study focuses on in-game advertising possibilities, identification, function, and logic in the NFS computer game series. We conduct a content analysis of three releases of NFS to identify its use for promotional purposes in real terms.

A New Action-Based Reasoning Approach for Playing Chess

Many previous research studies have demonstrated game strategies enabling virtual players to play and take actions mimicking humans.The CaseBased Reasoning(CBR)strategy tries to simulate human thinking regarding solving problems based on constructed knowledge.This paper suggests a new Action-Based Reasoning(ABR)strategy for a chess engine.This strategy mimics human experts’approaches when playing chess,with the help of the CBR phases.This proposed engine consists of the following processes.Firstly,an action library compiled by parsing many grandmasters’cases with their actions from different games is built.Secondly,this library reduces the search space by using two filtration steps based on the defined action-based and encoding-based similarity schemes.Thirdly,the minimax search tree is fed with a list extracted from the filtering stage using the alpha-beta algorithm to prune the search.The proposed evaluation function estimates the retrievably reactive moves.Finally,the best move will be selected,played on the board,and stored in the action library for future use.Many experiments were conducted to evaluate the performance of the proposed engine.Moreover,the engine played 200 games against Rybka 2.3.2a scoring 2500,2300,2100,and 1900 rating points.Moreover,they used the Bayeselo tool to estimate these rating points of the engine.The results illustrated that the proposed approach achieved high rating points,reaching as high as 2483 points.

Developing a Fuzzy Logic Based Game System

The fuzzy logic, which is a technique of the artificial intelligence, rises as a result of studies based on simulating the human brain. It is a type of logic that recognizes more than simple true and false values. Linguistic variables can be represented with degrees of truthfulness and falsehood by using fuzzy logic. Like other artificial intelligence techniques, the fuzzy logic is used in many different areas. In computer game industry, it can be used to develop artificial intelligence based games. In this paper, the author discusses about usage of the fuzzy logic technique in computer games and developed a basic game based on the fuzzy logic. In this game, a computer controlled character can behave differently according to changing situations.

Automatic acquisition of pattern collocations in GO

The quality, quantity, and consistency of the knowledge used in GO-playing programs often determine their strengths, and automatic acquisition of large amounts of high-quality and consistent GO knowledge is crucial for successful GO playing. In a previous article of this subject, we have presented an algorithm for efficient and automatic acquisition of spatial patterns of GO as well as their frequency of occurrence from game records. In this article, we present two algorithms, one for efficient and automatic acquisition of pairs of spatial patterns that appear jointly in a local context, and the other for deter- mining whether the joint pattern appearances are of certain significance statistically and not just a coincidence. Results of the two algorithms include 1 779 966 pairs of spatial patterns acquired automatically from 16 067 game records of professsional GO players, of which about 99.8% are qualified as pattern collocations with a statistical confidence of 99.5% or higher.

Automatic pattern acquisition from game records in GO

Computer programs of GO are typically constructed using a knowledge-based approach with heuristics and pattern matching because of enormous complexities of the game. In this approach, quantity, quality, and consistency of patterns used in computer programs of GO to a large extent determine the strengths of the programs. This study presents an effective method to acquire automatically comprehensive GO patterns from large collections of game records. Statistical usages of the patterns ensure consistency and quality of the patterns, which in turn can help improve the strengths of computer GO programs. Additionally, statistical usages of patterns from different sources of game records clearly show subtle and significant discrepancies among various types of GO players, and clarify certain myths in the playing of GO.