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JAY | Connect AI LAB on Instagram: "인공지능의 강화학습 분야에서는 의사결정 문제를 모델링하기 위한 수학적 구조로 주로 마르코프 결정 과정(Markov Decision Process, MDP)을 사용합니다. MDP는 상태(state), 행동(action), 보상(reward), 상태 전이 확률(state transition probability) 등을 포함하여 의사결정 과정을 수학적으로 모델링합니다. 이를 통해 에이전트는 주어진 환경에서 최적의 행동 정책을 학습할 수 있습니다. 더 복잡한 환경에서는 에이전트가 완전한 정보를 가지고 있지 않은 경우가 많습니다. 이런 상황을 모델링하기 위해 부분 관측 마르코프 결정 과정(Partially Observable Markov Decision Process, POMDP)이 사용됩니다. POMDP는 에이전트가 모든 상태 정보를 정확히 알 수 없고, 관측을 통해 얻은 정보를 바탕으로 결정을 내려야 하는 상황을 다룹니다.
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