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About

Stevan Tomic is a robotics and artificial intelligence researcher whose work centers on the critical challenge of enabling robots to understand, reason about, and adhere to human social norms. His research spans human-aware planning, normative reasoning, and the integration of robots into human social environments — fields that are increasingly vital as autonomous systems become embedded in everyday life. Tomic's most influential contribution, "Too Cool for School" (2014, 12 citations), introduced a pioneering method for extending human-aware planning to incorporate social constraints, allowing robots to adapt their behavior to complex interpersonal contexts. Building on this foundation, his 2018 body of work explored the application of institutional frameworks to mixed human-robot societies, investigating how normative structures can govern robot behavior in ways that mirror human social contracts (garnering 8 and 3 citations respectively). More recently, Tomic advanced the field by demonstrating how reinforcement learning can be guided by prior normative knowledge to produce socially compliant robot behavior, as detailed in "Learning Normative Behaviors Through Abstraction" (2020). Collectively, his research addresses a fundamental question in modern robotics: not merely what robots *can* do, but what they *should* do when sharing space with people.