2 citations · 3 across the 4 of their papers we have counts for
4 papers
HAVA: Hybrid Approach to Value-Alignment through Reward Weighing for Reinforcement Learning
Kryspin Varys, Federico Cerutti, Adam Sobey +1
Our society is governed by a set of norms which together bring about the values we cherish such as safety, fairness or trustworthiness. The goal of value-alignment is to create age…
CHIRPs: Change-Induced Regret Proxy metrics for Lifelong Reinforcement Learning
John Birkbeck, Adam Sobey, Federico Cerutti +2
Reinforcement learning (RL) agents are costly to train and fragile to environmental changes. They often perform poorly when there are many changing tasks, prohibiting their widespr…
Speaking Your Language: Spatial Relationships in Interpretable Emergent Communication
Olaf Lipinski, Adam J. Sobey, Federico Cerutti +1
Effective communication requires the ability to refer to specific parts of an observation in relation to others. While emergent communication literature shows success in developing…
Combinatorial Client-Master Multiagent Deep Reinforcement Learning for Task Offloading in Mobile Edge Computing
Tesfay Zemuy Gebrekidan, Sebastian Stein, Timothy J. Norman
Recently, there has been an explosion of mobile applications that perform computationally intensive tasks such as video streaming, data mining, virtual reality, augmented reality,…