Aditi Mishra
Papers
1
Total Citations
4
H-Index
1
About
Aditi Mishra is a rising researcher at the intersection of artificial intelligence and human-computer interaction, with a primary focus on explainable reinforcement learning (XRL). Her work addresses a critical challenge: how to make the decision-making processes of RL agents transparent and interpretable to non-expert users. In her most-cited paper, "Why? Why not? When? Visual Explanations of Agent Behavior in Reinforcement Learning" (2021), Mishra introduces novel frameworks for generating visual explanations that clarify not just what an agent did, but why it chose a particular action, why it avoided alternatives, and when such decisions are likely to occur. This contribution is vital for building trust in autonomous systems used in domains like self-driving cars, robotics, and finance. Though early in her career, her work has already garnered attention, with citations reflecting growing interest in ethical and accessible AI. Mishra’s research stands out for its user-centric approach, aiming to bridge the gap between complex algorithmic behavior and human understanding—a key step toward responsible deployment of intelligent agents in high-stakes environments.
Research Focus
Key Achievements
Top Papers
- 1