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#expert-demonstrations News & Analysis

2 articles tagged with #expert-demonstrations. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles
AINeutralarXiv – CS AI · May 116/10
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Multi-Objective Constraint Inference using Inverse reinforcement learning

Researchers introduce MOCI (Multi-Objective Constraint Inference), a novel framework that uses inverse reinforcement learning to extract safety constraints and individual preferences from diverse expert demonstrations where multiple experts have different objectives. The approach addresses limitations in existing methods that assume homogeneous expert behavior and offers improved computational efficiency.

AINeutralarXiv – CS AI · Mar 27/1013
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Learning to maintain safety through expert demonstrations in settings with unknown constraints: A Q-learning perspective

Researchers propose SafeQIL, a new Q-learning algorithm that learns safe policies from expert demonstrations in constrained environments where safety constraints are unknown. The approach balances maximizing task rewards while maintaining safety by learning from demonstrated trajectories that successfully complete tasks without violating hidden constraints.