RELAXED PROXIMAL POINT ALGORITHM FOR MONOTONE INCLUSION PROBLEM BEYOND MONOTONICITY

In this paper, we introduce a relaxed proximal point algorithm for solving the generalized inclusion problem involving a maximally comonotone operator in the framework of real Hilbert spaces.While the classical theory for the proximal point algorithm relies heavily on monotonicity assumptions, we demonstrate how comonotonicity (a weaker yet structurally rich property) provides sufficient conditions for convergence.By exploiting the fundamental connection between comonotonicity and averaged resolvents, we establish weak convergence of our proposed method under standard assumptions.