-
Scalable methods for computing state similarity in deterministic Markov Decision Processes
We present new algorithms for computing and approximating bisimulation m...
11/21/2019 ∙ by Pablo Samuel Castro, et al. ∙
49
∙
share
read it
-
Distributional reinforcement learning with linear function approximation
Despite many algorithmic advances, our theoretical understanding of prac...
02/08/2019 ∙ by Marc G. Bellemare, et al. ∙
18
∙
share
read it
-
A Geometric Perspective on Optimal Representations for Reinforcement Learning
This paper proposes a new approach to representation learning based on g...
01/31/2019 ∙ by Marc G. Bellemare, et al. ∙
10
∙
share
read it
-
Shaping the Narrative Arc: An Information-Theoretic Approach to Collaborative Dialogue
We consider the problem of designing an artificial agent capable of inte...
01/31/2019 ∙ by Kory W. Mathewson, et al. ∙
8
∙
share
read it
-
A Comparative Analysis of Expected and Distributional Reinforcement Learning
Since their introduction a year ago, distributional approaches to reinfo...
01/30/2019 ∙ by Clare Lyle, et al. ∙
6
∙
share
read it
-
An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents
Much human and computational effort has aimed to improve how deep reinfo...
12/17/2018 ∙ by Felipe Petroski Such, et al. ∙
6
∙
share
read it
-
Inverse Reinforcement Learning with Multiple Ranked Experts
We consider the problem of learning to behave optimally in a Markov Deci...
07/31/2019 ∙ by Pablo Samuel Castro, et al. ∙
5
∙
share
read it
-
Dopamine: A Research Framework for Deep Reinforcement Learning
Deep reinforcement learning (deep RL) research has grown significantly i...
12/14/2018 ∙ by Pablo Samuel Castro, et al. ∙
1
∙
share
read it
-
Combining Learned Lyrical Structures and Vocabulary for Improved Lyric Generation
The use of language models for generating lyrics and poetry has received...
11/12/2018 ∙ by Pablo Samuel Castro, et al. ∙
0
∙
share
read it
-
Performing Structured Improvisations with pre-trained Deep Learning Models
The quality of outputs produced by deep generative models for music have...
04/30/2019 ∙ by Pablo Samuel Castro, et al. ∙
0
∙
share
read it
-
Rigging the Lottery: Making All Tickets Winners
Sparse neural networks have been shown to be more parameter and compute ...
11/25/2019 ∙ by Utku Evci, et al. ∙
0
∙
share
read it
