[HTML][HTML] Artificial intelligence for video game visualization, advancements, benefits and challenges

Y Wu, A Yi, C Ma, L Chen - Mathematical Biosciences and …, 2023‏ - aimspress.com
In recent years, the field of artificial intelligence (AI) has witnessed remarkable progress and
its applications have extended to the realm of video games. The incorporation of AI in video …

[کتاب][B] Artificial intelligence and games

GN Yannakakis, J Togelius - 2018‏ - Springer
Georgios N. Yannakakis Julian Togelius Page 1 Artificial Intelligence and Games Georgios N.
Yannakakis Julian Togelius Page 2 Artificial Intelligence and Games Page 3 Georgios N …

Online minimax Q network learning for two-player zero-sum Markov games

Y Zhu, D Zhao - IEEE Transactions on Neural Networks and …, 2020‏ - ieeexplore.ieee.org
The Nash equilibrium is an important concept in game theory. It describes the least
exploitability of one player from any opponents. We combine game theory, dynamic …

Creating pro-level AI for a real-time fighting game using deep reinforcement learning

I Oh, S Rho, S Moon, S Son, H Lee… - IEEE Transactions on …, 2021‏ - ieeexplore.ieee.org
Reinforcement learning (RL) combined with deep neural networks has performed
remarkably well in many genres of games recently. It has surpassed human-level …

Enhanced rolling horizon evolution algorithm with opponent model learning: Results for the fighting game AI competition

Z Tang, Y Zhu, D Zhao, SM Lucas - IEEE Transactions on …, 2020‏ - ieeexplore.ieee.org
The Fighting Game AI Competition (FTGAIC) provides a challenging benchmark for two-
player video game artificial intelligence. The challenge arises from the large action space …

Monte-carlo tree search for implementation of dynamic difficulty adjustment fighting game ais having believable behaviors

M Ishihara, S Ito, R Ishii, T Harada… - … IEEE Conference on …, 2018‏ - ieeexplore.ieee.org
In this paper, we propose a Monte-Carlo Tree Search (MCTS) fighting game AI capable of
dynamic difficulty adjustment while maintaining believable behaviors. This work targets …

Evolving population method for real-time reinforcement learning

MJ Kim, JS Kim, CW Ahn - Expert Systems with Applications, 2023‏ - Elsevier
Reinforcement learning has recently been recognized as a promising means of machine
learning, but its applicability remains limited in real-time environment due to its short …

Hierarchical reinforcement learning with monte carlo tree search in computer fighting game

IP Pinto, LR Coutinho - IEEE transactions on games, 2018‏ - ieeexplore.ieee.org
Fighting games are complex environments where challenging action-selection problems
arise, mainly due to a diversity of opponents and possible actions. In this paper, we present …

[HTML][HTML] Audience participation fighting game: Exploring social facilitation for an enhanced APG experience

P Paliyawan, R Thawonmas, K Sookhanaphibarn… - Heliyon, 2024‏ - cell.com
This paper discusses the popularity of live streaming video games and its potential to
address psychological challenges, especially during the COVID-19 pandemic. An audience …

Hybrid fighting game AI using a genetic algorithm and Monte Carlo tree search

MJ Kim, CW Ahn - Proceedings of the genetic and evolutionary …, 2018‏ - dl.acm.org
Real-time video game problems are very challenging because of short response times and
numerous state space issues. As global companies and research institutes such as Google …