Poramate Manoonpong

This paper shows that the timing of forces in a robotic tug-of-war determines the outcome, with lagging teams winning under certain conditions, and introduces a decentralized control rule for cooperative transport.

The paper constructs a neural network model of the stick insect's walking system to explain phase transitions in motor activity observed in isolated ganglia.

This paper combines spiking and non-spiking neurons to create a sensorimotor pathway that shapes network output based on analog input, validated through simulation.

This paper presents a computational model of neural mechanisms for reward-modulated vector learning and navigation in embodied agents, linking behavioral observations to potential neural substrates.