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intrinsic reward

103 papers

Papers

Learning to Generate via Understanding: Understanding-Driven Intrinsic Rewarding for Unified Multimodal Models CVPR 2026 Reinforcement Learning Without Explicit Rewards: Theory and Practice AAAI 2026 Agent-Aware Training for Agent-Agnostic Action Advising in Deep Reinforcement Learning AAAI 2025 Constructive Conflict-Driven Multi-Agent Reinforcement Learning for Strategic Diversity IJCAI 2025 Curiosity-Driven Reinforcement Learning from Human Feedback ACL 2025 DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search ICLR 2025 Efficient Exploration and Discriminative World Model Learning with an Object-Centric Abstraction ICLR 2025 Episodic Novelty Through Temporal Distance ICLR 2025 GeoExplorer: Active Geo-localization with Curiosity-Driven Exploration ICCV 2025 MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization ICLR 2025 Moral Alignment for LLM Agents ICLR 2025 R3DM: Enabling Role Discovery and Diversity Through Dynamics Models in Multi-agent Reinforcement Learning ICML 2025 Toward Efficient Multi-Agent Exploration With Trajectory Entropy Maximization ICLR 2025 Towards Improving Exploration through Sibling Augmented GFlowNets ICLR 2025 Unsupervised Zero-Shot Reinforcement Learning via Dual-Value Forward-Backward Representation ICLR 2025 VCA: Video Curious Agent for Long Video Understanding ICCV 2025 World Models with Hints of Large Language Models for Goal Achieving NAACL 2025 DGPO: Discovering Multiple Strategies with Diversity-Guided Policy Optimization AAAI 2024 Effective Exploration Based on the Structural Information Principles NeurIPS 2024 Imagine, Initialize, and Explore: An Effective Exploration Method in Multi-Agent Reinforcement Learning AAAI 2024 Improving Intrinsic Exploration by Creating Stationary Objectives ICLR 2024 Intrinsic Action Tendency Consistency for Cooperative Multi-Agent Reinforcement Learning AAAI 2024 LAGMA: LAtent Goal-guided Multi-Agent Reinforcement Learning ICML 2024 Leveraging Mutual Information for Asymmetric Learning under Partial Observability CoRL 2024 Leveraging Separated World Model for Exploration in Visually Distracted Environments NeurIPS 2024