Efficient Exploration

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

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Libraries

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Datasets archive 2025-07-28

3 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

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Most implemented papers archive 2025-07-28

30 shown of 189 papers with code (514 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Noisy Networks for Exploration
  30 Jun 2017 15 repositories listed Syntology ran 1 of 3 samples · 2 unverified · 3 pointer-only (licence)
  We introduce NoisyNet, a deep reinforcement learning agent with parametric noise added to its weights, and show that the induced stochasticity of the agent's policy can be used to aid efficient exploration.
• Automatic chemical design using a data-driven continuous representation of molecules
  7 Oct 2016 11 repositories listed Syntology ran 5 of 26 samples · 21 unverified · 7 pointer-only (licence)
  We report a method to convert discrete representations of molecules to and from a multidimensional continuous representation.
• Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables
  19 Mar 2019 7 repositories listed Syntology ran 6 of 9 samples · 3 unverified · 1 pointer-only (licence)
  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.
• Stochastic Gradient Hamiltonian Monte Carlo
  17 Feb 2014 7 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  Hamiltonian Monte Carlo (HMC) sampling methods provide a mechanism for defining distant proposals with high acceptance probabilities in a Metropolis-Hastings framework, enabling more efficient exploration of the state…
• Deep Exploration via Bootstrapped DQN
  15 Feb 2016 6 repositories listed Syntology ran 1 of 2 samples · 1 unverified · 2 pointer-only (licence)
  Efficient exploration in complex environments remains a major challenge for reinforcement learning.
• Neural Contextual Bandits with UCB-based Exploration
  11 Nov 2019 4 repositories listed
  To the best of our knowledge, it is the first neural network-based contextual bandit algorithm with a near-optimal regret guarantee.
• Data-Efficient Exploration, Optimization, and Modeling of Diverse Designs through Surrogate-Assisted Illumination
  13 Feb 2017 4 repositories listed
  The MAP-Elites algorithm produces a set of high-performing solutions that vary according to features defined by the user.
• Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent
  5 Feb 2024 3 repositories listed Syntology ran 3 of 7 samples · 4 unverified
  We propose HyperAgent, a reinforcement learning (RL) algorithm based on the hypermodel framework for exploration in RL.
• Online Limited Memory Neural-Linear Bandits with Likelihood Matching
  7 Feb 2021 3 repositories listed Syntology ran 1 of 6 samples · 5 unverified
  To alleviate this, we propose a likelihood matching algorithm that is resilient to catastrophic forgetting and is completely online.
• Shared Experience Actor-Critic for Multi-Agent Reinforcement Learning
  12 Jun 2020 3 repositories listed
  Exploration in multi-agent reinforcement learning is a challenging problem, especially in environments with sparse rewards.
• Scaling MAP-Elites to Deep Neuroevolution
  3 Mar 2020 3 repositories listed
  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…
• ConEx: Efficient Exploration of Big-Data System Configurations for Better Performance
  17 Oct 2019 3 repositories listed
  For cost reduction, we developed and experimentally tested and validated two approaches: using scaled-up big data jobs as proxies for the objective function for larger jobs and using a dynamic job similarity measure to…
• Scheduled Policy Optimization for Natural Language Communication with Intelligent Agents
  16 Jun 2018 3 repositories listed
  We investigate the task of learning to follow natural language instructions by jointly reasoning with visual observations and language inputs.
• Scalable Exploration via Ensemble++
  18 Jul 2024 2 repositories listed Syntology ran 5 of 8 samples · 3 unverified · 8 pointer-only (licence)
  Thompson Sampling is a principled method for balancing exploration and exploitation, but its real-world adoption faces computational challenges in large-scale or non-conjugate settings.
• Streamlining Ocean Dynamics Modeling with Fourier Neural Operators: A Multiobjective Hyperparameter and Architecture Optimization Approach
  7 Apr 2024 2 repositories listed Syntology ran 3 of 4 samples · 1 unverified
  The experimental results show that the optimal set of hyperparameters enhanced model performance in single timestepping forecasting and greatly exceeded the baseline configuration in the autoregressive rollout for…
• Hierarchical Spatial Proximity Reasoning for Vision-and-Language Navigation
  18 Mar 2024 2 repositories listed
  To address this issue, we propose a Hierarchical Spatial Proximity Reasoning (HSPR) method.
• Demonstration-Guided Reinforcement Learning with Efficient Exploration for Task Automation of Surgical Robot
  20 Feb 2023 2 repositories listed
  Task automation of surgical robot has the potentials to improve surgical efficiency.
• Online Decision Transformer
  11 Feb 2022 2 repositories listed Syntology ran 2 of 2 samples · 0 unverified
  Recent work has shown that offline reinforcement learning (RL) can be formulated as a sequence modeling problem (Chen et al., 2021; Janner et al., 2021) and solved via approaches similar to large-scale language modeling.
• Episodic Multi-agent Reinforcement Learning with Curiosity-Driven Exploration
  22 Nov 2021 2 repositories listed
  Efficient exploration in deep cooperative multi-agent reinforcement learning (MARL) still remains challenging in complex coordination problems.
• Paradiseo: From a Modular Framework for Evolutionary Computation to the Automated Design of Metaheuristics ---22 Years of Paradiseo---
  2 May 2021 2 repositories listed
  The success of metaheuristic optimization methods has led to the development of a large variety of algorithm paradigms.
• State Entropy Maximization with Random Encoders for Efficient Exploration
  18 Feb 2021 2 repositories listed
  Recent exploration methods have proven to be a recipe for improving sample-efficiency in deep reinforcement learning (RL).
• BeBold: Exploration Beyond the Boundary of Explored Regions
  15 Dec 2020 2 repositories listed
  In this paper, we analyze the pros and cons of each method and propose the regulated difference of inverse visitation counts as a simple but effective criterion for IR.
• Hybrid Genetic Search for the CVRP: Open-Source Implementation and SWAP* Neighborhood
  23 Nov 2020 2 repositories listed
  The vehicle routing problem is one of the most studied combinatorial optimization topics, due to its practical importance and methodological interest.
• Self-Supervised Exploration via Disagreement
  10 Jun 2019 2 repositories listed
  In this paper, we propose a formulation for exploration inspired by the work in active learning literature.
• Estimating Risk and Uncertainty in Deep Reinforcement Learning
  23 May 2019 2 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  Reinforcement learning agents are faced with two types of uncertainty.
• Learning Exploration Policies for Navigation
  5 Mar 2019 2 repositories listed
  Numerous past works have tackled the problem of task-driven navigation.
• Model-Based Active Exploration
  29 Oct 2018 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  Efficient exploration is an unsolved problem in Reinforcement Learning which is usually addressed by reactively rewarding the agent for fortuitously encountering novel situations.
• NSGA-Net: Neural Architecture Search using Multi-Objective Genetic Algorithm
  8 Oct 2018 2 repositories listed
  This paper introduces NSGA-Net -- an evolutionary approach for neural architecture search (NAS).
• Count-Based Exploration with the Successor Representation
  31 Jul 2018 2 repositories listed Syntology ran 0 of 2 samples · 2 unverified
  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…
• Randomized Value Functions via Multiplicative Normalizing Flows
  6 Jun 2018 2 repositories listed
  In particular, we augment DQN and DDPG with multiplicative normalizing flows in order to track a rich approximate posterior distribution over the parameters of the value function.

Syntology lines on 13 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.