Add to ORKGThis work presents a scalable solution to automate game-testing. Traditionally, game-testing has been performed by either human players or scripted Artificial Intelligence (AI) agents. While the first produces the most reliable results, the process of organizing testing sessions is time consuming. On the other hand, scripted AI dramatically speeds up the process, however, the insights it provides are far less useful: these agents’ behaviors are highly predictable. The presented solution takes the best of both worlds: the automation of scripted AI, and the richness of human testing by framing the problem within the Deep Reinforcement Learning (DRL) paradigm. Reinforcement Learning (RL) agents are trained to adapt to any unseen level and pres...
I denna rapport implementerar vi en reinforcement learning (RL) algoritm som lär sig spela Breakout ...
I denna rapport implementerar vi en reinforcement learning (RL) algoritm som lär sig spela Breakout ...
I denna rapport implementerar vi en reinforcement learning (RL) algoritm som lär sig spela Breakout ...
This work presents a scalable solution to automate game-testing. Traditionally, game-testing has bee...
Games are commonly used as playground for AI research, specifically in the field of Reinforcement Le...
Games are commonly used as playground for AI research, specifically in the field of Reinforcement Le...
Reinforcement Learning is a promising approach to develop intelligent agents that can help game deve...
Following the success that machine learning has enjoyed over the last decade, reinforcement learning...
Following the success that machine learning has enjoyed over the last decade, reinforcement learning...
In this thesis, we used deep reinforcement learning to train autonomous agents and evaluated the imp...
In this thesis, we used deep reinforcement learning to train autonomous agents and evaluated the imp...
In this thesis, we used deep reinforcement learning to train autonomous agents and evaluated the imp...
In this thesis we present two approaches to improve automatic playtesting using player modeling. By ...
In this thesis we present two approaches to improve automatic playtesting using player modeling. By ...
In this thesis we present two approaches to improve automatic playtesting using player modeling. By ...
I denna rapport implementerar vi en reinforcement learning (RL) algoritm som lär sig spela Breakout ...
I denna rapport implementerar vi en reinforcement learning (RL) algoritm som lär sig spela Breakout ...
I denna rapport implementerar vi en reinforcement learning (RL) algoritm som lär sig spela Breakout ...
This work presents a scalable solution to automate game-testing. Traditionally, game-testing has bee...
Games are commonly used as playground for AI research, specifically in the field of Reinforcement Le...
Games are commonly used as playground for AI research, specifically in the field of Reinforcement Le...
Reinforcement Learning is a promising approach to develop intelligent agents that can help game deve...
Following the success that machine learning has enjoyed over the last decade, reinforcement learning...
Following the success that machine learning has enjoyed over the last decade, reinforcement learning...
In this thesis, we used deep reinforcement learning to train autonomous agents and evaluated the imp...
In this thesis, we used deep reinforcement learning to train autonomous agents and evaluated the imp...
In this thesis, we used deep reinforcement learning to train autonomous agents and evaluated the imp...
In this thesis we present two approaches to improve automatic playtesting using player modeling. By ...
In this thesis we present two approaches to improve automatic playtesting using player modeling. By ...
In this thesis we present two approaches to improve automatic playtesting using player modeling. By ...
I denna rapport implementerar vi en reinforcement learning (RL) algoritm som lär sig spela Breakout ...
I denna rapport implementerar vi en reinforcement learning (RL) algoritm som lär sig spela Breakout ...
I denna rapport implementerar vi en reinforcement learning (RL) algoritm som lär sig spela Breakout ...