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The Role of Transitions and Contrastive Loss in Reinforcement Learning
This chapter discusses the role of transitions in reinforcement learning and how they are encoded in a graph neural network. It also explores the concept of contrastive loss and its use in ensuring states with similar properties have the same optimal action.