Citation Impact
Citing Papers
Reinforcement learning as classification: leveraging modern classifiers
2003
Coordinated Reinforcement Learning
2002
A comprehensive survey on safe reinforcement learning
2015 Standout
Dynamic programming for partially observable stochastic games
2004
Solving very large weakly coupled Markov decision processes
1998
Monte-Carlo exploration for deterministic planning
2009
Reinforcement Learning with Hierarchies of Machines
1997
Transfer Learning via Inter-Task Mappings for Temporal Difference Learning
2007
Online Ensemble Learning
2000
Safe Policy Iteration
2013
Reinforcement Learning with Factored States and Actions
2004 StandoutNobel
Nonlinear Boosting Projections for Ensemble Construction
2007
Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts
2007
Is multiagent deep reinforcement learning the answer or the question? A brief survey
2018
Transfer Learning for Reinforcement Learning Domains: A Survey
2009
Clinical-grade computational pathology using weakly supervised deep learning on whole slide images
2019 Standout
Ensemble learning for data stream analysis: A survey
2017
Recent advances in physical reservoir computing: A review
2019 Standout
Recent Advances in Hierarchical Reinforcement Learning
2003
Mastering the game of Go without human knowledge
2017 StandoutNatureNobel
Computational pathology: Challenges and promises for tissue analysis
2011
Human-level control through deep reinforcement learning
2015 StandoutNatureNobel
AdaBoost-Based Algorithm for Network Intrusion Detection
2008
Recurrent temporal networks and language acquisition—from corticostriatal neurophysiology to reservoir computing
2013
Deep learning in histopathology: the path to the clinic
2021 Standout
Projective simulation with generalization
2017
Constructing Ensembles of Classifiers by Means of Weighted Instance Selection
2009
Learn$^{++}$.NC: Combining Ensemble of Classifiers With Dynamically Weighted Consult-and-Vote for Efficient Incremental Learning of New Classes
2008
Reinforcement Learning Versus Model Predictive Control: A Comparison on a Power System Problem
2008
Deep learning in neural networks: An overview
2014 Standout
Machine learning: Trends, perspectives, and prospects
2015 StandoutScience
The Impact of Diversity on Online Ensemble Learning in the Presence of Concept Drift
2009
A Survey on Ensemble Learning for Data Stream Classification
2017
Online Adaboost-Based Parameterized Methods for Dynamic Distributed Network Intrusion Detection
2013
Human–agent collaboration for disaster response
2015
Reinforcement learning in robotics: A survey
2013 Standout
Deep Learning Approach for Intelligent Intrusion Detection System
2019 Standout
Active learning machine learns to create new quantum experiments
2018 StandoutNobel
A survey of robot learning from demonstration
2008 Standout
An object-oriented representation for efficient reinforcement learning
2008
Object tracking
2006 Standout
Reinforcement learning for building controls: The opportunities and challenges
2020 Standout
Multi-agent reinforcement learning as a rehearsal for decentralized planning
2016
Dynamic scheduling for flexible job shop with new job insertions by deep reinforcement learning
2020 Standout
On-Line Building Energy Optimization Using Deep Reinforcement Learning
2018 Standout
SPUDD: Stochastic Planning using Decision Diagrams
2013
Ensemble-based classifiers
2009 Standout
Deep Reinforcement Learning for Multiagent Systems: A Review of Challenges, Solutions, and Applications
2020 Standout
A Comprehensive Survey on Transfer Learning
2020 Standout
DDD: A New Ensemble Approach for Dealing with Concept Drift
2011
Trust Region Policy Optimization
2015 Standout
Big Data Analytics in Intelligent Transportation Systems: A Survey
2018 Standout
Hybrid decision tree
2002
Boosting for class-imbalanced datasets using genetically evolved supervised non-linear projections
2012
A combinational incremental ensemble of classifiers as a technique for predicting students’ performance in distance education
2010
Survey of intrusion detection systems: techniques, datasets and challenges
2019 Standout
Robust Object Tracking with Online Multiple Instance Learning
2010 Standout
Hierarchical multi-agent reinforcement learning
2006
The empirical case for two systems of reasoning.
1996 Standout
Communication-Efficient Policy Gradient Methods for Distributed Reinforcement Learning
2021
Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications
2021 Standout
Integrating Guidance into Relational Reinforcement Learning
2004
Human Trust in Artificial Intelligence: Review of Empirical Research
2020 Standout
Robust Control of Markov Decision Processes with Uncertain Transition Matrices
2005
Ensemble of online neural networks for non-stationary and imbalanced data streams
2013
Apple Leaf Diseases Recognition Based on An Improved Convolutional Neural Network
2020 Standout
Précis ofDeduction
1993
A survey on ensemble learning
2019 Standout
Acquisition of chess knowledge in AlphaZero
2022 StandoutNobel
Lower Bounding Klondike Solitaire with Monte-Carlo Planning
2009
A Survey of Monte Carlo Tree Search Methods
2012 Standout
Predicting students' final performance from participation in on-line discussion forums
2013 Standout
Dynamic Programming and Suboptimal Control: A Survey from ADP to MPC*
2005
Learning from class-imbalanced data: Review of methods and applications
2016 Standout
Recent Advances in Hierarchical Reinforcement Learning
2003
Multiagent Learning of Coordination in Loosely Coupled Multiagent Systems
2015
A Comprehensive Survey of Multiagent Reinforcement Learning
2008 Standout
Decision-Theoretic Planning: Structural Assumptions and Computational Leverage
1999
Automated handwashing assistance for persons with dementia using video and a partially observable Markov decision process
2010 Standout
Deep Reinforcement Learning: A Brief Survey
2017 Standout
Hierarchical Solution of Markov Decision Processes using Macro-actions
2013
Online neural network model for non-stationary and imbalanced data stream classification
2013
Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning
1999 Standout
SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary
2018 Standout
Decision trees: a recent overview
2011 Standout
Percentile Optimization for Markov Decision Processes with Parameter Uncertainty
2009
A survey and critique of multiagent deep reinforcement learning
2019
Stochastic dynamic programming with factored representations
2000
Data mining in education
2012 Standout
Accelerating Reinforcement Learning through Implicit Imitation
2003
A survey on concept drift adaptation
2014 Standout
Cyber-physical systems architectures for industrial internet of things applications in Industry 4.0: A literature review
2020 Standout
A survey of transfer learning
2016 Standout
Incremental learning with multi-level adaptation
2011
Recommender system application developments: A survey
2015 Standout
Distributed policy search reinforcement learning for job-shop scheduling tasks
2011
Survey on Unmanned Aerial Vehicle Networks: A Cyber Physical System Perspective
2019
Evolution and Intelligent Design
2008 StandoutNobel
Theory and Applications of Robust Optimization
2011 Standout
Shaping multi-agent systems with gradient reinforcement learning
2007
Chemical gas sensor drift compensation using classifier ensembles
2012 Standout
Ensemble learning: A survey
2018 Standout
TLdR: Policy Summarization for Factored SSP Problems Using Temporal Abstractions
2020
A Roadmap of Agent Research and Development
1998 Standout
Mining the Situation: Spatiotemporal Traffic Prediction With Big Data
2015
Control Techniques for Complex Networks
2007
Works of Robert Givan being referenced
Model minimization in Markov decision processes
1997
FF-Replan: a baseline for probabilistic planning
2007
Natural Language Based Inference Procedures Applied to Schubert''s Steamroller
1991
Approximate Policy Iteration with a Policy Language Bias
2003
Model minimization, regression, and propositional STRIPS planning
1997
Probabilistic planning via determinization in hindsight
2008
Online Ensemble Learning: An Empirical Study
2000
Learning domain-specific control knowledge from random walks
2004
Specific-to-General Learning for Temporal Events with Application to Learning Event Definitions from Video
2002
Approximate Policy Iteration with a Policy Language Bias: Solving Relational Markov Decision Processes
2006
Inductive Policy Selection for First-Order MDPs
2012
Online Ensemble Learning: An Empirical Study
2003
Model Reduction Techniques for Computing Approximately Optimal Solutions for Markov Decision Processes
2013
Relational Reinforcement Learning: An Overview
2004
Parallel Rollout for Online Solution of Partially Observable Markov Decision Processes
2004
Approximate Policy Iteration with a Policy Language Bias: Learning Control Knowledge Planning in Planning Domains
2003
Bounded-parameter Markov decision processes
2000
The Complexity of Decentralized Control of Markov Decision Processes
2002