Interactive training is a technique that allows humans to guide a learning algorithm. This technique is well suited to training first person shooter bots as it allows game designers to iterate a range of behaviors in real-time. This paper investigates an initial attempt at allowing users to interact with the learning process of a reinforcement learning algorithm to create first person shooter bot behaviors. The results clearly show that it is possible to create different types of bot behaviors using the developed interactive training tool
Abstract—The aim of intelligent techniques, termed game AI, used in computer video games is to provi...
Abstract. Modern video games present many challenging applications for artificial intelligence. Agen...
It is our goal to understand the role real-time human in-teraction can play in machine learning algo...
This paper demonstrates the applicability of reinforcement learning for first person shooter bot art...
Interactive training is well suited to computer games as it allows game designers to interact with o...
Reinforcement learning is well suited to first person shooter bot artificial intelligence as it has ...
The goal of this thesis is to explore the use of reinforcement learning (RL) in commercial computer ...
In current state-of-the-art commercial first person shooter games, computer controlled bots, also kn...
Machine learning is now widely studied as thebasis for artificial intelligence systems within comput...
The creation of effective autonomous agents (bots) for combat scenarios has long been a goal of the ...
Reinforcement learning (RL) is a paradigm which involves an agent interacting with an environment. T...
This project uses Unity3D as the game engine for building a first person shooter game, the Zombie Hu...
The creation of effective autonomous agents (bots) for combat scenarios has long been a goal of the ...
Training agents to play in contemporary multiplayer actions game is a challenging task, especially w...
This paper argues that natural interaction with a machine can be realized and improved by using lear...
Abstract—The aim of intelligent techniques, termed game AI, used in computer video games is to provi...
Abstract. Modern video games present many challenging applications for artificial intelligence. Agen...
It is our goal to understand the role real-time human in-teraction can play in machine learning algo...
This paper demonstrates the applicability of reinforcement learning for first person shooter bot art...
Interactive training is well suited to computer games as it allows game designers to interact with o...
Reinforcement learning is well suited to first person shooter bot artificial intelligence as it has ...
The goal of this thesis is to explore the use of reinforcement learning (RL) in commercial computer ...
In current state-of-the-art commercial first person shooter games, computer controlled bots, also kn...
Machine learning is now widely studied as thebasis for artificial intelligence systems within comput...
The creation of effective autonomous agents (bots) for combat scenarios has long been a goal of the ...
Reinforcement learning (RL) is a paradigm which involves an agent interacting with an environment. T...
This project uses Unity3D as the game engine for building a first person shooter game, the Zombie Hu...
The creation of effective autonomous agents (bots) for combat scenarios has long been a goal of the ...
Training agents to play in contemporary multiplayer actions game is a challenging task, especially w...
This paper argues that natural interaction with a machine can be realized and improved by using lear...
Abstract—The aim of intelligent techniques, termed game AI, used in computer video games is to provi...
Abstract. Modern video games present many challenging applications for artificial intelligence. Agen...
It is our goal to understand the role real-time human in-teraction can play in machine learning algo...