Non-player character decision-making in computer games
MÇ Uludağlı, K Oğuz - Artificial Intelligence Review, 2023 - Springer
One of the most overlooked challenges in artificial intelligence (AI) for computer games is to
create non-player game characters (NPCs) with human-like behavior. Modern NPCs …
create non-player game characters (NPCs) with human-like behavior. Modern NPCs …
Artificial intelligence and virtual worlds–toward human-level AI agents
VM Petrović - IEEE Access, 2018 - ieeexplore.ieee.org
Artificial Intelligence (AI) has a long tradition as a scientific field, with tremendous
achievements accomplished in the decades behind us. At the same time, in the last few …
achievements accomplished in the decades behind us. At the same time, in the last few …
[图书][B] Motivated reinforcement learning: curious characters for multiuser games
KE Merrick, ML Maher - 2009 - books.google.com
Motivated learning is an emerging research field in artificial intelligence and cognitive
modelling. Computational models of motivation extend reinforcement learning to adaptive …
modelling. Computational models of motivation extend reinforcement learning to adaptive …
Genetic Algorithm Applications for Challenging Real-World Problems: Some Recent Advances and Future Trends
A Iglesias, A Gálvez - Applied Genetic Algorithm and Its Variants: Case …, 2023 - Springer
Originated from the work of J. Holland in the 70s, genetic algorithms have become one of the
most popular and widely used computational developments for optimization and global …
most popular and widely used computational developments for optimization and global …
Crowd simulation via multi-agent reinforcement learning
L Torrey - Proceedings of the AAAI Conference on Artificial …, 2010 - ojs.aaai.org
Artificial intelligence is frequently used to control virtual characters in movies and games.
When these characters appear in crowds, controlling them is called crowd simulation. In this …
When these characters appear in crowds, controlling them is called crowd simulation. In this …
Constrained environment optimization for prioritized multi-agent navigation
Traditional approaches for multi-agent navigation consider the environment as a fixed
constraint, despite the obvious influence of spatial constraints on agents' performance. Yet …
constraint, despite the obvious influence of spatial constraints on agents' performance. Yet …
Multi-agent path finding in configurable environments
M Bellusci, N Basilico, F Amigoni - PROCEEDINGS OF THE …, 2020 - air.unimi.it
Abstract Multi-Agent Path Finding (MAPF) plays an important role in many real-life
applications where autonomous agents must coordinate to reach their goals without …
applications where autonomous agents must coordinate to reach their goals without …
Neural network trojan
A Geigel - Journal of Computer Security, 2013 - content.iospress.com
This paper presents a proof of concept of a neural network Trojan. The neural network
Trojan consists of a neural network that has been trained with a compromised dataset and …
Trojan consists of a neural network that has been trained with a compromised dataset and …
Tuning computer gaming agents using q-learning
The aim of intelligent techniques, termed game AI, used in computer video games is to
provide an interesting and challenging game play to a game player. Being highly …
provide an interesting and challenging game play to a game player. Being highly …
Motivated reinforcement learning for adaptive characters in open-ended simulation games
KE Merrick, ML Maher - Proceedings of the international conference on …, 2007 - dl.acm.org
Recently a new generation of virtual worlds has emerged in which users are provided with
open-ended modelling tools with which they can create and modify world content. The result …
open-ended modelling tools with which they can create and modify world content. The result …