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Policy Learning

2068 directly classified papers

Papers per year

Papers

HCPO: Hierarchical Conductor-Based Policy Optimization in Multi-Agent Reinforcement Learning AAAI 2026
Policy Newton Methods for Distortion Riskmetrics AAAI 2026
T4NMTD: Transition-Centric Reinforcement Learning for Non-Markovian Task Decomposition AAAI 2026
Stabilizing Policy Gradient Methods via Reward Profiling AAAI 2026
Client Selection for Federated Policy Optimization with Environment Heterogeneity JMLR 2025
Convergence and Sample Complexity of Natural Policy Gradient Primal-Dual Methods for Constrained MDPs JMLR 2025
Multi-Teacher Knowledge Distillation with Reinforcement Learning for Visual Recognition AAAI 2025
Score-Aware Policy-Gradient and Performance Guarantees using Local Lyapunov Stability JMLR 2025
Principled Penalty-based Methods for Bilevel Reinforcement Learning and RLHF JMLR 2025
On the Convergence of Projected Policy Gradient for Any Constant Step Sizes JMLR 2025
A Deployed Online Reinforcement Learning Algorithm in an Oral Health Clinical Trial AAAI 2025
The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise JMLR 2025
Simple Policy Optimization ICML 2025
Continuously evolving rewards in an open-ended environment JMLR 2025
Logarithmic Regret for Linear Markov Decision Processes with Adversarial Corruptions AAAI 2025
Semi-Markovian Planning to Coordinate Aerial and Maritime Medical Evacuation Platforms AAAI 2025
Online MDP with Prototypes Information: A Robust Adaptive Approach AAAI 2025
Statistical field theory for Markov decision processes under uncertainty JMLR 2025
On-Policy Algorithms for Continual Reinforcement Learning (Student Abstract) AAAI 2025
ModelDiff: Symbolic Dynamic Programming for Model-Aware Policy Transfer in Deep Q-Learning AAAI 2025
Defending Against Sophisticated Poisoning Attacks with RL-based Aggregation in Federated Learning AAAI 2025
Leveraging Human Input to Enable Robust, Interactive, and Aligned AI Systems AAAI 2025
Representation-driven Option Discovery in Reinforcement Learning AAAI 2025
The POWER of Ikigai: Optimizing Life Fulfillment with an Integrated User Simulator and Adaptive Hobby Recommender AAAI 2025
Formally Verified Approximate Policy Iteration AAAI 2025