当前标签：RL

RealWorld Games Look Like Spinning Tops

initial_h 2021-08-30 14:02 阅读:234 评论:0 推荐:0

Reinforcement Learning as One Big Sequence Modeling Problem

initial_h 2021-08-28 05:31 阅读:424 评论:0 推荐:0

A graph placement methodology for fast chip design

initial_h 2021-08-26 00:14 阅读:501 评论:0 推荐:0

MEASURING THE RELIABILITY OF REINFORCEMENT LEARNING ALGORITHMS

initial_h 2021-08-23 08:15 阅读:104 评论:0 推荐:0

Decision Transformer: Reinforcement Learning via Sequence Modeling

initial_h 2021-08-21 09:21 阅读:881 评论:0 推荐:0

Learning and Planning in Complex Action Spaces

initial_h 2021-08-19 02:12 阅读:275 评论:0 推荐:0

Vector Quantized Models for Planning

initial_h 2021-08-16 06:39 阅读:221 评论:0 推荐:0

Neural Discrete Representation Learning(VQ-VAE)

initial_h 2021-08-10 06:29 阅读:1472 评论:0 推荐:0

Online and Offline Reinforcement Learning by Planning with a Learned Model

initial_h 2021-08-07 13:23 阅读:436 评论:2 推荐:0

BEBOLD: EXPLORATION BEYOND THE BOUNDARY OF EXPLORED REGIONS

initial_h 2021-08-04 23:45 阅读:164 评论:0 推荐:0

The NetHack Learning Environment

initial_h 2021-08-01 01:05 阅读:145 评论:0 推荐:0

Convex Regularization in Monte-Carlo Tree Search

initial_h 2021-07-29 23:54 阅读:132 评论:0 推荐:0

From Motor Control to Team Play in Simulated Humanoid Football

initial_h 2021-07-27 13:26 阅读:225 评论:0 推荐:0

Behaviour Suite for Reinforcement Learning（bsuite）

initial_h 2021-07-23 04:50 阅读:140 评论:0 推荐:0

OFF-POLICY ACTOR-CRITIC WITH SHARED EXPERIENCE REPLAY（LASER）

initial_h 2021-07-21 13:58 阅读:150 评论:0 推荐:0

Safe and efficient off-policy reinforcement learning（Retrace）

initial_h 2021-07-20 02:06 阅读:259 评论:0 推荐:0

MAXIMUM A POSTERIORI POLICY OPTIMISATION (MPO)

initial_h 2021-07-16 00:23 阅读:657 评论:0 推荐:0

Using Monte Carlo Tree Search as a Demonstrator within Asynchronous Deep RL

initial_h 2021-07-14 11:43 阅读:106 评论:0 推荐:0

Observe and Look Further: Achieving Consistent Performance on Atari

initial_h 2021-07-10 01:51 阅读:240 评论:0 推荐:0

RECURRENT EXPERIENCE REPLAY IN DISTRIBUTED REINFORCEMENT LEARNING（R2D2）

initial_h 2021-07-05 09:11 阅读:215 评论:0 推荐:0