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Reinforcement Learning › Methods ›

Deep RL

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Papers

DIMM: Decoupled Multi-hierarchy Kalman Filter via Reinforcement Learning AAAI 2026

Keep On Going: Learning Robust Humanoid Motion Skills via Selective Adversarial Training AAAI 2026

D²PPO: Diffusion Policy Policy Optimization with Dispersive Loss AAAI 2026

DiffOP: Reinforcement Learning of Optimization-Based Control Policies via Implicit Policy Gradients AAAI 2026

GINO-Q: Learning an Asymptotically Optimal Index Policy for Restless Multi-armed Bandits AAAI 2026

MS-PPO: Mean Standard Deviation Proximal Policy Optimization for Reliable Parking Space Search in Structured Environments AAAI 2026

Risk-Sensitive Exponential Actor Critic AAAI 2026

Out-of-Distribution Generalization with a SPARC: Racing 100 Unseen Vehicles with a Single Policy AAAI 2026

Variance Reduction via Resampling and Experience Replay AAAI 2026

Reliability-Guaranteed and Reward-Seeking Sequence Modeling for Model-Based Offline Reinforcement Learning AAAI 2026

Gradient-Protected Value Decomposition for Cooperative Multi-Agent Reinforcement Learning AAAI 2026

Beyond Monotonicity: Revisiting Factorization Principles in Multi-Agent Q-Learning AAAI 2026

Enhancing Diffusion Policies with Distribution-Matching Generator in Offline Reinforcement Learning AAAI 2026

Policy Zooming: Adaptive Discretization-based Infinite-Horizon Average-Reward Reinforcement Learning AAAI 2026

CHDP: Cooperative Hybrid Diffusion Policies for Reinforcement Learning in Parameterized Action Space AAAI 2026

Perceiving the Knowledge Boundary: Uncertainty-Guided Exploration and Imagination for World Models AAAI 2026

Learning Branching Policies for MILPs with Proximal Policy Optimization AAAI 2026

T4NMTD: Transition-Centric Reinforcement Learning for Non-Markovian Task Decomposition AAAI 2026

Context-Sensitive Abstractions for Reinforcement Learning with Parameterized Actions AAAI 2026

Object-Centric World Models for Causality-Aware Reinforcement Learning AAAI 2026

Do It for HER: First-Order Temporal Logic Reward Specification in Reinforcement Learning AAAI 2026

A Differential Perspective on Distributional Reinforcement Learning AAAI 2026

Improving Stochastic Action-Constrained Reinforcement Learning via Truncated Distributions AAAI 2026

Planning in Branch-and-Bound: Model-Based Reinforcement Learning for Exact Combinatorial Optimization AAAI 2026

Beyond Training-time Poisoning: Component-level and Post-training Backdoors in Deep Reinforcement Learning AAAI 2026