Papers
6
Total Citations
221
H-Index
6
About
Domenico Parisi is a computational researcher whose work spans robotics, artificial intelligence, and cognitive science, with particular expertise in evolutionary robotics, collective behavior, and reinforcement learning. His most influential contribution, "Distributed Coordination of Simulated Robots Based on Self-Organization" (2006, 101 citations), demonstrated how groups of robots can accomplish complex tasks without centralized leadership, relying instead on self-organizing principles drawn from the study of animal and human collective behavior. Building on this foundation, his 2003 and 2004 work on physically linked robot teams explored how coordinated motion, obstacle avoidance, and behavioral integration emerge in cooperative robotic systems. Parisi has also made notable contributions to learning and cognition, proposing a bioinspired hierarchical reinforcement learning architecture capable of acquiring multiple skills while avoiding catastrophic interference — a persistent challenge in machine learning. His interdisciplinary reach extends into behavioral neuroscience, with research comparing gambling behavior across rodents, primates, and robots to illuminate the mechanisms underlying pathological gambling in humans. Across his career, Parisi bridges computational modeling and biological inspiration, offering researchers and students a compelling template for using simulated agents to probe some of the most fundamental questions in collective intelligence and adaptive behavior.
Research Focus
Key Achievements
Top Papers
- 1Distributed Coordination of Simulated Robots Based on Self-Organization101 citations · 2006
- 2Nonhuman gamblers: lessons from rodents, primates, and robots38 citations · 2014
- 3Evolution of Collective Behavior in a Team of Physically Linked Robots34 citations · 2003
- 4
- 5Coordination and Behaviour Integration in Cooperating Simulated Robots16 citations · 2004
- 6