2 articles tagged with #model-free. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.
Researchers have introduced AIQI (Universal AI with Q-Induction), the first model-free artificial intelligence agent proven to be asymptotically optimal in general reinforcement learning. Unlike previous optimal agents like AIXI that rely on environment models, AIQI performs universal induction over distributional action-value functions, significantly expanding the diversity of known universal agents.
Researchers present a novel harmonic mean formulation for average reward reinforcement learning in Semi-Markov decision processes (SMDPs), addressing a critical gap where existing algorithms fail under non-stationary reward and duration distributions. The new approach enables more robust model-free learning algorithms for infinite-horizon tasks where traditional reward-to-duration ratio optimization becomes mathematically incorrect.
