2 citations · 6 across the 8 of their papers we have counts for
6 papers · 1 filter
Partial Models for Building Adaptive Model-Based Reinforcement Learning Agents
Safa Alver, Ali Rahimi-Kalahroudi, Doina Precup
In neuroscience, one of the key behavioral tests for determining whether a subject of study exhibits model-based behavior is to study its adaptiveness to local changes in the envir…
Minimal Value-Equivalent Partial Models for Scalable and Robust Planning in Lifelong Reinforcement Learning
Safa Alver, Doina Precup
Learning models of the environment from pure interaction is often considered an essential component of building lifelong reinforcement learning agents. However, the common practice…
A Look at Value-Based Decision-Time vs. Background Planning Methods Across Different Settings
Safa Alver, Doina Precup
In model-based reinforcement learning (RL), an agent can leverage a learned model to improve its way of behaving in different ways. Two of the prevalent ways to do this are through…
Constructing a Good Behavior Basis for Transfer using Generalized Policy Updates
Safa Alver, Doina Precup
We study the problem of learning a good set of policies, so that when combined together, they can solve a wide variety of unseen reinforcement learning tasks with no or very little…
What is Going on Inside Recurrent Meta Reinforcement Learning Agents?
Safa Alver, Doina Precup
Recurrent meta reinforcement learning (meta-RL) agents are agents that employ a recurrent neural network (RNN) for the purpose of "learning a learning algorithm". After being train…
A Brief Look at Generalization in Visual Meta-Reinforcement Learning
Safa Alver, Doina Precup
Due to the realization that deep reinforcement learning algorithms trained on high-dimensional tasks can strongly overfit to their training environments, there have been several st…