The GitHub repository for "Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo", AISTATS 2024.
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Oct 19, 2024 - Python
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exploration-exploitation
Here are 28 public repositories matching this topic...
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Mar 27, 2022 - Python
over-parameterization = exploration ?
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Aug 23, 2020 - Python
Repository Containing Comparison of two methods for dealing with Exploration-Exploitation dilemma for MultiArmed Bandits
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Jul 2, 2021 - Python
A reinforcement learning project where a snake learns to navigate and survive in a dynamic environment through Q-learning.
reinforcement-learning neural-network tensorflow keras q-learning snake-game exploration-exploitation ai-agent
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Apr 16, 2025 - Python
A systematic parameter study of exploration–exploitation trade-offs in an Active Inference agent under varying precision and sensory noise.
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Jan 14, 2026 - Python
Uses GloVe embeddings + bandit-style exploration/exploitation with adaptive diversification, UCB-driven cluster search, and stagnation recovery.
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Aug 29, 2025 - Python
PyTorch-native contextual bandits with Neural Thompson Sampling for scalable exploration and large action sets.
python pytorch thompson-sampling experimentation multi-armed-bandits online-learning contextual-bandits bayesian-linear-regression bandit-algorithms replay-buffer exploration-exploitation neural-linear two-tower
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Feb 7, 2026 - Python
Deep Intrinsically Motivated Exploration in Continuous Control
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Mar 2, 2024 - Python
Official implementation of LECO (NeurIPS'22)
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May 11, 2023 - Python
This project focuses on comparing different Reinforcement Learning Algorithms, including monte-carlo, q-learning, lambda q-learning epsilon-greedy variations, etc.
python reinforcement-learning monte-carlo openai-gym q-learning policy rl-agents epsilon-greedy dynamic-programming markov-chains approximation-algorithms ucb1 q-lambda exploration-exploitation thomson-sampling frozen-lake multi-bandit-army
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Feb 15, 2022 - Python
This is an implementation of the Reinforcement Learning multi-arm-bandit experiment using different exploration techniques.
reinforcement-learning reinforcement-learning-algorithms bandit-algorithms exploration-exploitation exploration-strategy
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Oct 4, 2021 - Python
This repository collects reference code for several multi-agent and distributed contextual bandit algorithms.
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Nov 25, 2025 - Python
🤖 Explore and optimize rewards with Bandexa, a PyTorch-native library for Neural-Linear Thompson Sampling in contextual bandits.
python pytorch thompson-sampling experimentation multi-armed-bandits online-learning contextual-bandits bayesian-linear-regression bandit-algorithms replay-buffer exploration-exploitation neural-linear two-tower
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Apr 19, 2026 - Python
Explore the 10-Arm Testbed Simulation! 🎲 Utilize Python to test various ε-greedy strategies in a reinforcement learning environment. Visualize and compare agents' performance as they balance exploration and exploitation. Perfect for learners and enthusiasts! 🚀📊
python machine-learning reinforcement-learning decision-making epsilon-greedy multi-armed-bandit exploration-exploitation
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May 27, 2024 - Python
MACE-RL is a novel framework that learns to dynamically regulate its own exploration strategy. It integrates a curiosity module, informed by episodic memory of past experiences, with a meta-learning network that monitors the agent's performance and adaptively regulates the influence of the intrinsic curiosity bonus.
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Jan 20, 2026 - Python
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Dec 17, 2019 - Python
The official code release for "More Efficient Randomized Exploration for Reinforcement Learning via Approximate Sampling", Reinforcement Learning Conference (RLC) 2024
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Jun 19, 2024 - Python
Research Thesis - Reinforcement Learning
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May 22, 2019 - Python
The official code release for Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo, ICLR 2024.
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Feb 19, 2026 - Python
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