In our work, we introduced the Anchored Value Iteration, which demonstrates accelerated rates for both the Bellman consistency and optimality operators, offering meaningful advancements in convergence algorithms for reinforcement learning.
We provide rigorous proofs of convergence with a focus on understanding the conditions under which our methods outperform existing alternatives, particularly in complex environments like those found in artificial intelligence.
#reinforcement-learning #value-iteration #convergence-rates #artificial-intelligence #mathematical-science
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