10 articles tagged with "Reinforcement Learning"
A new bitboard approach to Tetris AI enhances the efficiency of game engines and optimizes policy algorithms for reinforcement learning agents, according to recent research.
The AutoB2G framework leverages large language models and reinforcement learning to enhance building-grid co-simulation, addressing operational complexity.
A new method for AI-driven vector sketching has been developed, focusing on incremental production through a multi-turn reinforcement learning framework.
The newly introduced CRAFT framework aims to bolster AI model robustness by leveraging reasoning capabilities and hidden representations to defend against jailbreak attacks.
Ndea, part of the Y Combinator W26 cohort, is actively hiring for a symbolic reinforcement learning search guidance lead to advance its AI initiatives.
A recent study examines the necessity of diversity in aligning large language models (LLMs) through reinforcement learning with verifiable rewards (RLVR), focusing on moral reasoning.
A new approach leverages reinforcement learning and LLM-based quality assurance to optimize search strategies for missing children, focusing on the critical first 72 hours.
The introduction of autonomous AI agents utilizing shortfall aware reinforcement learning techniques could significantly impact derivatives market operations and hedging strategies.
The paper discusses the critical role of decision structures in reinforcement learning, particularly in multi-agent settings, and the implications for system architecture.
A new benchmark has been introduced to enhance reinforcement learning research by providing a middle ground between full games and mini-games in StarCraft II, addressing challenges in reward signals.