research
∙
08/18/2023
Learning Computational Efficient Bots with Costly Features
Deep reinforcement learning (DRL) techniques have become increasingly us...
share
research
∙
12/22/2021
Direct Behavior Specification via Constrained Reinforcement Learning
The standard formulation of Reinforcement Learning lacks a practical way...
research
∙
12/22/2021
Graph augmented Deep Reinforcement Learning in the GameRLand3D environment
We address planning and navigation in challenging 3D video games featuri...
research
∙
11/09/2020
Deep Reinforcement Learning for Navigation in AAA Video Games
In video games, non-player characters (NPCs) are used to enhance the pla...
research
∙
07/06/2020
TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning?
We investigate whether Jacobi preconditioning, accounting for the bootst...
research
∙
01/31/2020
Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning
Accurate reporting of energy and carbon usage is essential for understan...
research
∙
06/09/2019
Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning
Multi-simulator training has contributed to the recent success of Deep R...
research
∙
02/05/2019
Separating value functions across time-scales
In many finite horizon episodic reinforcement learning (RL) settings, it...
research
∙
10/26/2018
TarMAC: Targeted Multi-Agent Communication
We explore a collaborative multi-agent reinforcement learning setting wh...
research
∙
10/05/2018
Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods
Recent analyses of certain gradient descent optimization methods have sh...
research
∙
06/06/2018
Randomized Value Functions via Multiplicative Normalizing Flows
Randomized value functions offer a promising approach towards the challe...
research
∙
05/09/2018
Reward Estimation for Variance Reduction in Deep Reinforcement Learning
In reinforcement learning (RL), stochastic environments can make learnin...
research
∙
04/03/2017
Multi-Advisor Reinforcement Learning
We consider tackling a single-agent RL problem by distributing it to n l...
research
∙
12/15/2016
