13 citations · 31 across the 4 of their papers we have counts for
6 papers
Using Reward Uncertainty to Induce Diverse Behaviour in Reinforcement Learning
Anthony GX-Chen, Ankit Anand, Gheorghe Comanici +7
Classical reinforcement learning (RL) typically seeks a deterministic policy that maximizes the expected sum of a scalar reward. Yet, modern applications such as language model fin…
An AI system to help scientists write expert-level empirical software
Eser Aygün, Anastasiya Belyaeva, Gheorghe Comanici +39
The cycle of scientific discovery is frequently bottlenecked by the slow, manual creation of software to support computational experiments\cite{hannay2009how}. To address this, we…
The Option Keyboard: Combining Skills in Reinforcement Learning
André Barreto, Diana Borsa, Shaobo Hou +8
The ability to combine known skills to create new ones may be crucial in the solution of complex reinforcement learning problems that unfold over extended periods. We argue that a…
Learning to cooperate: Emergent communication in multi-agent navigation
Ivana Kajić, Eser Aygün, Doina Precup
Emergent communication in artificial agents has been studied to understand language evolution, as well as to develop artificial systems that learn to communicate with humans. We sh…
Spectral renormalization group theory on networks
Eser Aygun, Ayse Erzan
Discrete amorphous materials are best described in terms of arbitrary networks which can be embedded in three dimensional space. Investigating the thermodynamic equilibrium as well…
A Formal Treatment of Generalized Preferential Attachment and its Empirical Validation
Amac Herdagdelen, Eser Aygun, Haluk Bingol
Generalized preferential attachment is defined as the tendency of a vertex to acquire new links in the future with respect to a particular vertex property. Understanding which prop…