Agent learning in fully observable, continuous and real-time game environments

2016
Baykal, Ömer
Game industry has become one of the sectors that commonly use artificial intelli- gence. Today, most of the game environments need and include artificial intelligence agents to offer more challenging and entertaining experience. Development processes and the quality of artificial intelligence agents are the most important concerns in this area. Since it becomes harder to develop good agents as games become more com- plex, machine learning methods have started to be used in some notable games to shorten this development process and to improve the quality of agents. Popularity of machine learning applications in game environments has increased in last decades. Supervised learning is a machine learning method which can be applied to develop artificial intelligence agents that play a game like human players by imitating them. The imitating agents can either play the role of opponents or play on behalf of the real players when they are absent. The purpose of this study is to develop imitating agents for one of the world’s most played online game; HaxBall. The developed agents can mimic the real HaxBall players. HaxBall is a two dimensional football game with fully observable, continuous, and real time game environment. 

Suggestions

Supervised Learning in Football Game Environments Using Artificial Neural Networks
Baykal, Ömer; Alpaslan, Ferda Nur (2018-09-23)
Game industry has become one of the sectors that commonly use artificial intelligence. Today, most of the game environments include artificial intelligence agents to offer more challenging and entertaining gameplay experience. Since it gets harder to develop good agents as games become more complex, machine learning methods have started to be used in some notable games to shorten the development process of agents and to improve their quality. Popularity of machine learning applications in game environments ...
Machine learning methods for opponent modeling in games of imperfect information
Şirin, Volkan; Yarman Vural, Fatoş Tunay; Department of Computer Engineering (2012)
This thesis presents a machine learning approach to the problem of opponent modeling in games of imperfect information. The efficiency of various artificial intelligence techniques are investigated in this domain. A sequential game is called imperfect information game if players do not have all the information about the current state of the game. A very popular example is the Texas Holdem Poker, which is used for realization of the suggested methods in this thesis. Opponent modeling is the system that enabl...
DEVELOPMENT OF SCIENTIFIC SOFTWARE: A SYSTEMATIC MAPPING, A BIBLIOMETRICS STUDY, AND A PAPER REPOSITORY
Farhoodi, Roshanak; Garousi, Vahid; Pfahl, Dietmar; Sillito, Jonathan (World Scientific Pub Co Pte Lt, 2013-05-01)
Scientific and engineering research is heavily dependent on effective development and use of software artifacts. Many of these artifacts are produced by the scientists themselves, rather than by trained software engineers. To address the challenges in this area, a research community often referred to as "Development of Scientific Software" has emerged in the last few decades. As this research area has matured, there has been a sharp increase in the number of papers and results made available, and it has thu...
Context based dynamic content generation, introducing a new approach and a framework
Özdemir, Burkay; İşler, Veysi; Department of Modeling and Simulation (2015)
Game Industry is growing every day with thousands of games are being released each month. Although game development tools are constantly become more easy to use, accessible and carry most of the workload of developers, serving fresh content is still a big issue for developers. Procedural Content Generation (PCG) is used as an alternative method to providing content manually. Despite its main purposes like reducing the memory usage are fading away with the recent developments, it has a huge potential to crea...
Modeling student behaviors in a virtual classroom using belief desire intention model
Canbazoğlu, Emre; İşler, Veysi; Department of Modeling and Simulation (2014)
Agent and behavior modeling is one of the most important components of computer games and virtual environments that make these products more realistic and attractive. Agent and behavior modeling can also be used for serious games which is designed for training people in virtual interactive environments instead of real life training with less cost and close effectiveness. Belief-Desire-Intention(BDI) model is one of the software models that is used to model intelligent agents. In this thesis, we used BDI arc...
Citation Formats
Ö. Baykal, “Agent learning in fully observable, continuous and real-time game environments,” M.S. - Master of Science, Middle East Technical University, 2016.