In what ways can function approximation be utilized to address the curse of dimensionality in dynamic programming, and what are the potential risks associated with using function approximators in reinforcement learning?
Tuesday, 11 June 2024
by EITCA Academy
Function approximation serves as a pivotal tool in addressing the curse of dimensionality in dynamic programming, particularly within the context of reinforcement learning (RL) and Markov decision processes (MDPs). The curse of dimensionality refers to the exponential growth in computational complexity and memory requirements as the number of state and action variables increases. This phenomenon