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Efficient Exploration

32 papers with code ยท Methodology

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PBCS : Efficient Exploration and Exploitation Using a Synergy between Reinforcement Learning and Motion Planning

24 Apr 2020

In this paper, we propose a new algorithm called "Plan, Backplay, Chain Skills" (PBCS) that combines motion planning and reinforcement learning to solve hard exploration environments.

CONTINUOUS CONTROL EFFICIENT EXPLORATION MOTION PLANNING

Weakly-Supervised Reinforcement Learning for Controllable Behavior

6 Apr 2020

Reinforcement learning (RL) is a powerful framework for learning to take actions to solve tasks.

CONTINUOUS CONTROL EFFICIENT EXPLORATION

Bayesian optimisation of large-scale photonic reservoir computers

6 Apr 2020

We test this approach on a previously reported large-scale experimental system, compare it to the commonly used grid search, and report notable improvements in performance and the number of experimental iterations required to optimise the hyper-parameters.

BAYESIAN OPTIMISATION EFFICIENT EXPLORATION

Provably Efficient Exploration for RL with Unsupervised Learning

15 Mar 2020

We study how to use unsupervised learning for efficient exploration in reinforcement learning with rich observations generated from a small number of latent states.

EFFICIENT EXPLORATION

Active Model Estimation in Markov Decision Processes

6 Mar 2020

Using a number of simple domains with heterogeneous noise in their transitions, we show that our heuristic-based algorithm outperforms both our original algorithm and the maximum entropy algorithm in the small sample regime, while achieving similar asymptotic performance as that of the original algorithm.

COMMON SENSE REASONING EFFICIENT EXPLORATION

Efficient Exploration in Constrained Environments with Goal-Oriented Reference Path

3 Mar 2020

Specifically, we train a deep convolutional network that can predict collision-free paths based on a map of the environment-- this is then used by a reinforcement learning algorithm to learn to closely follow the path.

EFFICIENT EXPLORATION

Scaling MAP-Elites to Deep Neuroevolution

3 Mar 2020

Quality-Diversity (QD) algorithms, and MAP-Elites (ME) in particular, have proven very useful for a broad range of applications including enabling real robots to recover quickly from joint damage, solving strongly deceptive maze tasks or evolving robot morphologies to discover new gaits.

EFFICIENT EXPLORATION

Efficient exploration of zero-sum stochastic games

24 Feb 2020

We investigate the increasingly important and common game-solving setting where we do not have an explicit description of the game but only oracle access to it through gameplay, such as in financial or military simulations and computer games.

EFFICIENT EXPLORATION

Split-BOLFI for for misspecification-robust likelihood free inference in high dimensions

21 Feb 2020

To advance the possibilities for performing likelihood-free inference in high-dimensional parameter spaces, here we introduce an extension of the popular Bayesian optimisation based approach to approximate discrepancy functions in a probabilistic manner which lends itself to an efficient exploration of the parameter space.

BAYESIAN OPTIMISATION EFFICIENT EXPLORATION