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Efficient Exploration

24 papers with code · Methodology

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Receding Horizon Curiosity

8 Oct 2019mschulth/rhc

Sample-efficient exploration is crucial not only for discovering rewarding experiences but also for adapting to environment changes in a task-agnostic fashion.

EFFICIENT EXPLORATION

6
08 Oct 2019

Learning-Driven Exploration for Reinforcement Learning

17 Jun 2019Usama1002/EBE-Exploration

We introduce entropy-based exploration (EBE) that enables an agent to explore efficiently the unexplored regions of the state space.

EFFICIENT EXPLORATION FPS GAMES

0
17 Jun 2019

Efficient Exploration via State Marginal Matching

12 Jun 2019RLAgent/state-marginal-matching

We recast exploration as a problem of State Marginal Matching (SMM), where we aim to learn a policy for which the state marginal distribution matches a given target state distribution, which can incorporate prior knowledge about the task.

EFFICIENT EXPLORATION

31
12 Jun 2019

Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables

19 Mar 2019katerakelly/oyster

In our approach, we perform online probabilistic filtering of latent task variables to infer how to solve a new task from small amounts of experience.

EFFICIENT EXPLORATION

169
19 Mar 2019

Concurrent Meta Reinforcement Learning

7 Mar 2019impredicative/irc-rss-feed-bot

In this multi-agent setting, a set of parallel agents are executed in the same environment and each of these "rollout" agents are given the means to communicate with each other.

EFFICIENT EXPLORATION META-LEARNING MULTI-AGENT REINFORCEMENT LEARNING

5
07 Mar 2019

Playing Text-Adventure Games with Graph-Based Deep Reinforcement Learning

NAACL 2019 rajammanabrolu/KG-DQN

Text-based adventure games provide a platform on which to explore reinforcement learning in the context of a combinatorial action space, such as natural language.

EFFICIENT EXPLORATION QUESTION ANSWERING TRANSFER LEARNING

44
04 Dec 2018

Model-Based Active Exploration

29 Oct 2018nnaisense/max

Efficient exploration is an unsolved problem in Reinforcement Learning which is usually addressed by reactively rewarding the agent for fortuitously encountering novel situations.

EFFICIENT EXPLORATION

39
29 Oct 2018

NSGA-Net: Neural Architecture Search using Multi-Objective Genetic Algorithm

8 Oct 2018ianwhale/nsga-net

This paper introduces NSGA-Net -- an evolutionary approach for neural architecture search (NAS).

EFFICIENT EXPLORATION NEURAL ARCHITECTURE SEARCH OBJECT CLASSIFICATION

88
08 Oct 2018

Count-Based Exploration with the Successor Representation

ICLR 2019 mcmachado/count_based_exploration_sr

In this paper we introduce a simple approach for exploration in reinforcement learning (RL) that allows us to develop theoretically justified algorithms in the tabular case but that is also extendable to settings where function approximation is required.

ATARI GAMES EFFICIENT EXPLORATION

7
31 Jul 2018