Add to ORKGDeep reinforcement learning has learned to play many games well, but failed on others. To better characterize the modes and reasons of failure of deep reinforcement learners, we test the widely used Asynchronous Actor-Critic (A2C) algorithm on four deceptive games, which are specially designed to provide challenges to game-playing agents. These games are implemented in the General Video Game AI framework, which allows us to compare the behavior of reinforcement learningbased agents with planning agents based on tree search. We find that several of these games reliably deceive deep reinforcement learners, and that the resulting behavior highlights the shortcomings of the learning algorithm. The particular ways in which agents fail differ fro...
Since DeepMind pioneered a deep reinforcement learning (DRL) model to play the Atari games, DRL has ...
This article focuses on the recent advances in the field of reinforcement learning (RL) as well as t...
Recently, world-class human players have been outperformed in a number of complex two-person games (...
Deep reinforcement learning has learned to play many games well, but failed on others. To better cha...
Deep Learning methods are known to be vulnerable to adversarial attacks. Since Deep Reinforcement Le...
When interacting with fictional environments, the users' sense of immersion can be broken when chara...
© 2019 Neural information processing systems foundation. All rights reserved. Recent breakthroughs i...
We created a computer program that allowed users to play ``No Thanks! , a popular card game that is ...
Deceptive games are games where the reward structure or other aspects of the game are designed to le...
Video game AI to this day is a series of hardcoded responses to situations that may arise during the...
Deep networks have been successfully applied to a wide range of tasks in artificial intelligence, an...
Deep reinforcement learning (DRL) brings the power of deep neural networks to bear on the generic ta...
Real-time strategy (RTS) games have provided a fertile ground for AI research with notable recent su...
In recent years, deep neural networks for strategy games have made significant progress. AlphaZero-l...
Recent developments in deep reinforcement learning applied to abstract strategy games such as Go, ch...
Since DeepMind pioneered a deep reinforcement learning (DRL) model to play the Atari games, DRL has ...
This article focuses on the recent advances in the field of reinforcement learning (RL) as well as t...
Recently, world-class human players have been outperformed in a number of complex two-person games (...
Deep reinforcement learning has learned to play many games well, but failed on others. To better cha...
Deep Learning methods are known to be vulnerable to adversarial attacks. Since Deep Reinforcement Le...
When interacting with fictional environments, the users' sense of immersion can be broken when chara...
© 2019 Neural information processing systems foundation. All rights reserved. Recent breakthroughs i...
We created a computer program that allowed users to play ``No Thanks! , a popular card game that is ...
Deceptive games are games where the reward structure or other aspects of the game are designed to le...
Video game AI to this day is a series of hardcoded responses to situations that may arise during the...
Deep networks have been successfully applied to a wide range of tasks in artificial intelligence, an...
Deep reinforcement learning (DRL) brings the power of deep neural networks to bear on the generic ta...
Real-time strategy (RTS) games have provided a fertile ground for AI research with notable recent su...
In recent years, deep neural networks for strategy games have made significant progress. AlphaZero-l...
Recent developments in deep reinforcement learning applied to abstract strategy games such as Go, ch...
Since DeepMind pioneered a deep reinforcement learning (DRL) model to play the Atari games, DRL has ...
This article focuses on the recent advances in the field of reinforcement learning (RL) as well as t...
Recently, world-class human players have been outperformed in a number of complex two-person games (...