Reinforcement learning in aviation, either unmanned or manned, with an injection of AI

We propose a novel theme of aviation with the injection of AI in the form of a reinforcement learning (RL) agent that learns flying skills by observing the pilot’s psychological reaction and flight path in a simulator. The pilot and the RL agent learn flying skills simultaneously, forming a symbiotic relationship. The episodes for training the...

Temporary memory neuron for the leaky integrate and fire neuron model

Low-level terrain-following systems require the ability to rapidly and accurately respond to the environment to prevent inadvertent actions. Catastrophic and fatal results could occur if missed cues or latency issues in data processing are encountered. Spiking neural networks (SNNs) have the computational ability to continuously process spike...

Machine awareness

Current and future research that embodies a pathway to achieving machine common sense (MCS), including Capsule Neural Networks, Hebbian Plasticity Theory, Dual Process Theory, and machine awareness (MA). The final frontier may well involve a framework that is capable of machine curiosity, exploration, automatic selfdirection and adaptation. The...