Max Robotics — Global Service Robot Directory + US Certification

About

Ioannis Pisokas explores the intersection of robotics, artificial intelligence, and neuroscience, with a core focus on how biological systems can inspire more adaptive and efficient robotic control. His early work centered on subsymbolic action planning for mobile robots, investigating how robots can learn to plan actions using generalized representations of their experience rather than explicit symbolic rules. In a 2005 study, he compared three subsymbolic planners, contributing to foundational methods for enabling autonomous decision-making in real-world environments. More recently, Pisokas has turned to reverse engineering neural circuits, particularly in insects, as a tool for robotics. His 2021 paper, with five citations, argues that understanding neuronal circuits honed over millions of years for adaptive behavior can offer novel solutions to robotic challenges, leveraging modern genetic tools to map connectivity and function at the single-neuron level. While his citation counts are modest, Pisokas’s work bridges computational modeling and biological insight, offering a unique perspective on how evolved neural architectures can inform the next generation of autonomous systems.