Adi Makmal

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About

Adi Makmal is a leading researcher in the intersection of quantum physics and artificial intelligence, with a primary focus on developing novel models for intelligent agents. Her most significant contribution is her pioneering work on **Projective Simulation (PS)** , a framework for reinforcement learning that models an agent's decision-making process using episodic memory. Makmal’s research has been instrumental in advancing this model, particularly by introducing the critical capability of **generalization** into PS agents. Her 2017 paper, "Projective simulation with generalization" (43 citations), established that without this ability, agents cannot learn effectively in certain environments, outlining key criteria for building more robust AI. She further demonstrated the model's practical utility in her 2018 work, "Benchmarking Projective Simulation in Navigation Problems" (25 citations), which validated PS as a flexible and powerful tool for constructing reinforcement-learning agents. A hallmark of her research is exploring the **quantum mechanical generalization** of the PS model, which promises computational speedups. Through her work, Makmal has helped bridge the gap between quantum information science and machine learning, creating frameworks that are both theoretically elegant and practically relevant for next-generation AI.