3 citations · 4 across the 7 of their papers we have counts for
7 papers
Rapid Open-World Adaptation by Adaptation Principles Learning
Cheng Xue, Ekaterina Nikonova, Peng Zhang +1
Novelty adaptation is the ability of an intelligent agent to adjust its behavior in response to changes in its environment. This is an important characteristic of intelligent agent…
Efficient Open-world Reinforcement Learning via Knowledge Distillation and Autonomous Rule Discovery
Ekaterina Nikonova, Cheng Xue, Jochen Renz
Deep reinforcement learning suffers from catastrophic forgetting and sample inefficiency making it less applicable to the ever-changing real world. However, the ability to use prev…
NovPhy: A Testbed for Physical Reasoning in Open-world Environments
Chathura Gamage, Vimukthini Pinto, Cheng Xue +4
Due to the emergence of AI systems that interact with the physical environment, there is an increased interest in incorporating physical reasoning capabilities into those AI system…
Don't do it: Safer Reinforcement Learning With Rule-based Guidance
Ekaterina Nikonova, Cheng Xue, Jochen Renz
During training, reinforcement learning systems interact with the world without considering the safety of their actions. When deployed into the real world, such systems can be dang…
Measuring Difficulty of Novelty Reaction
Ekaterina Nikonova, Cheng Xue, Vimukthini Pinto +3
Current AI systems are designed to solve close-world problems with the assumption that the underlying world is remaining more or less the same. However, when dealing with real-worl…
Phy-Q as a measure for physical reasoning intelligence
Cheng Xue, Vimukthini Pinto, Chathura Gamage +3
Humans are well-versed in reasoning about the behaviors of physical objects and choosing actions accordingly to accomplish tasks, while it remains a major challenge for AI. To faci…
Deep Q-Network for Angry Birds
Ekaterina Nikonova, Jakub Gemrot
Angry Birds is a popular video game in which the player is provided with a sequence of birds to shoot from a slingshot. The task of the game is to destroy all green pigs with maxim…