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Enhanced rolling horizon evolution algorithm with opponent model learning: Results for the fighting game AI competition
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 …
player video game artificial intelligence. The challenge arises from the large action space …
Evolving population method for real-time reinforcement learning
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 …
learning, but its applicability remains limited in real-time environment due to its short …
Adaptive traffic signal control system using composite reward architecture based deep reinforcement learning
The increasing traffic congestion problem can be solved by an adaptive traffic signal control
(ATSC) system as it utilises real‐time traffic information to control traffic signals. Recently …
(ATSC) system as it utilises real‐time traffic information to control traffic signals. Recently …
Time-varying weights in multi-reward architecture for deep reinforcement learning
Deep Reinforcement Learning (DRL) has recently been focused on extracting more
knowledge from the reward signal to improve sample efficiency. The Multi-Reward …
knowledge from the reward signal to improve sample efficiency. The Multi-Reward …
A deep reinforcement learning blind AI in DareFightingICE
This paper presents a deep reinforcement learning agent (AI) that uses sound as the input
on the DareFightingICE platform at the DareFightingICE Competition in IEEE CoG 2022. In …
on the DareFightingICE platform at the DareFightingICE Competition in IEEE CoG 2022. In …
AI Games and Algorithms: An Overview of Categories
AI games are one of the growing fields along with the advancement of computing
technologies. Many computer games have been deployed as AI games. To the best of our …
technologies. Many computer games have been deployed as AI games. To the best of our …
Mastering fighting game using deep reinforcement learning with self-play
DW Kim, S Park, S Yang - 2020 IEEE Conference on Games …, 2020 - ieeexplore.ieee.org
One-on-one fighting game has played a role as a bridge between board game and real-time
simulation game in terms of research on game AI because it needs middle-level …
simulation game in terms of research on game AI because it needs middle-level …
Surrogate-assisted Monte Carlo Tree Search for real-time video games
Abstract Monte Carlo Tree Search (MCTS) is a pronounced empirical search algorithm for
agent decision-making, especially when enhanced by Deep Learning (DL), in mastering …
agent decision-making, especially when enhanced by Deep Learning (DL), in mastering …
A fighting game AI using highlight cues for generation of entertaining gameplay
In this paper, we propose a fighting game AI that selects its actions from the perspective of
highlight generation using Monte-Carlo tree search (MCTS) with three highlight cues in the …
highlight generation using Monte-Carlo tree search (MCTS) with three highlight cues in the …
Evolving artificial neural networks for multi-objective tasks
Neuroevolution represents a growing research field in Artificial and Computational
Intelligence. The adjustment of the network weights and the topology is usually based on a …
Intelligence. The adjustment of the network weights and the topology is usually based on a …