Exploration Strategy

Exploration strategy in reinforcement learning and robotics focuses on efficiently finding optimal solutions in complex, often unknown environments, balancing the exploration of new states with the exploitation of known rewards. Current research emphasizes improving sample efficiency through techniques like action persistence, novelty-based exploration, and adaptive methods that dynamically adjust exploration based on the agent's internal state or learned value functions, often utilizing Bayesian methods or deep reinforcement learning architectures. These advancements have significant implications for various applications, including autonomous navigation, search and rescue operations, and multi-robot collaboration, by enabling more efficient learning and improved performance in challenging scenarios.

Papers

September 9, 2024

State-Novelty Guided Action Persistence in Deep Reinforcement Learning
Jianshu Hu, Paul Weng, Yutong Ban
Deep Reinforcement Learning Action Repetition Exploration Strategy Persistence Image

July 10, 2024

Distributed multi-robot potential-field-based exploration with submap-based mapping and noise-augmented strategy
Khattiya Pongsirijinda, Zhiqiang Cao, Kaushik Bhowmik, Muhammad Shalihan, Billy Pik Lik Lau, Ran Liu, Chau Yuen, U-Xuan Tan
Multi Robot Autonomous Exploration Exploration Method Exploration Strategy Based Exploration Harnessing Inherent Noise

June 12, 2024

Improving Policy Optimization via $\varepsilon$-Retrain
Luca Marzari, Changliu Liu, Priya L. Donti, Enrico Marchesini
Model Retraining Exploration Strategy Efficient Policy Learning

June 6, 2024

Gait-Adaptive Navigation and Human Searching in field with Cyborg Insect
Phuoc Thanh Tran-Ngoc, Huu Duoc Nguyen, Duc Long Le, Rui Li, Bing Sheng Chong, Hirotaka Sato
Environment Exploration Limited Field Search Behavior Exploration Strategy Cyborg Insect

March 26, 2024

VDSC: Enhancing Exploration Timing with Value Discrepancy and State Counts
Marius Captari, Remo Sasso, Matthia Sabatelli
Deep Reinforcement Learning Efficient Exploration Task Discrepancy Exploration Strategy Epsilon Greedy Exploration Time

January 31, 2024

Behind the Myth of Exploration in Policy Gradients
Adrien Bolland, Gaspard Lambrechts, Damien Ernst
Policy Gradient Optimal Policy Environment Exploration Near Optimal Policy Policy Gradient Algorithm Exploration Strategy Many Myth Effective Reinforcement Learning

October 5, 2023

LESSON: Learning to Integrate Exploration Strategies for Reinforcement Learning via an Option Framework
Woojun Kim, Jeonghye Kim, Youngchul Sung
Reinforcement Learning Exploration Exploitation Trade Exploration Strategy Instructional Design Option Learning

September 28, 2023

Comparing Active Learning Performance Driven by Gaussian Processes or Bayesian Neural Networks for Constrained Trajectory Exploration
Sapphira Akins, Frances Zhu
Active Learning Gaussian Process Bayesian Neural Network Autonomous Robot Active Learning Algorithm Exploration Strategy Intelligent Exploration Constrained Exploration

July 5, 2023

First-Explore, then Exploit: Meta-Learning to Solve Hard Exploration-Exploitation Trade-Offs
Ben Norman, Jeff Clune
Exploration Problem Exploration Policy Exploration Strategy Intelligent Exploration

June 9, 2023

The Role of Diverse Replay for Generalisation in Reinforcement Learning
Max Weltevrede, Matthijs T. J. Spaan, Wendelin Böhmer
Reinforcement Learning Zero Shot Strong Generalization Multi Task Integral Role Exploration Strategy

June 8, 2023

On the Importance of Exploration for Generalization in Reinforcement Learning
Yiding Jiang, J. Zico Kolter, Roberta Raileanu
Reinforcement Learning Deep Reinforcement Learning Strong Generalization Environment Exploration Importance Aware Distributional Learning Exploration Strategy

April 11, 2023

Simulation Analysis of Exploration Strategies and UAV Planning for Search and Rescue
Phuoc Nguyen Thuan, Jorge Peña Queralta, Tomi Westerlund
Unmanned Aerial Vehicle Search Query Search and Rescue Multi UAV Exploration Strategy Simulation Model Aerial Scene Classification

October 11, 2022

The Role of Exploration for Task Transfer in Reinforcement Learning
Jonathan C Balloch, Julia Kim, and Jessica L Inman, Mark O Riedl
Reinforcement Learning Integral Role Environment Exploration Exploration Method Exploration Exploitation Trade Exploration Strategy

July 16, 2022

Scene Graph for Embodied Exploration in Cluttered Scenario
Yuhong Deng, Qie Sima, Di Guo, Huaping Liu, Yi Wang, Fuchun Sun
Robot Person Scene Graph Robotics Community Cluttered Scene Exploration Strategy

May 2, 2022

Exploration in Deep Reinforcement Learning: A Survey
Pawel Ladosz, Lilian Weng, Minwoo Kim, Hyondong Oh
Reinforcement Learning Timely Survey Deep Reinforcement Learning Environment Exploration Sparse Reward Exploration Method Exploration Strategy

April 20, 2022

Exploration strategies for articulatory synthesis of complex syllable onsets
Daniel R. van Niekerk, Anqi Xu, Branislav Gerazov, Paul K. Krug, Peter Birkholz, Yi Xu
Exploration Strategy Pitch Contour Articulatory Signal Articulatory Synthesis Natural Language Specification

March 2, 2022

Follow your Nose: Using General Value Functions for Directed Exploration in Reinforcement Learning
Durgesh Kalwar, Omkar Shelke, Somjit Nath, Hardik Meisheri, Harshad Khadilkar
Reinforcement Learning Value Function Sparse Reward Exploration Method Exploration Strategy Directed Exploration

February 24, 2022

Collaborative Training of Heterogeneous Reinforcement Learning Agents in Environments with Sparse Rewards: What and When to Share?
Alain Andres, Esther Villar-Rodriguez, Javier Del Ser
Environment Feature Sparse Reward Intrinsic Reward Heterogeneous Agent Intrinsic Motivation Reinforcement Learning Environment Collaborative Training Exploration Strategy Heterogeneous Multi Agent Reinforcement Learning

December 21, 2021

Adversarial Gradient Driven Exploration for Deep Click-Through Rate Prediction
Kailun Wu, Zhangming Chan, Weijie Bian, Lejian Ren, Shiming Xiang, Shuguang Han, Hongbo Deng, Bo Zheng
Click Through Rate Prediction Active Exploration Exploration Strategy Large Scale Recommender System Generative Adversarial Exploration

November 3, 2021

Online Learning of Energy Consumption for Navigation of Electric Vehicles
Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani
Online Learning Local Navigation Energy Consumption Electric Vehicle Road Network Efficient Navigation Exploration Strategy