Abstract: A pilot support system includes: a processing circuit; and memory storing instructions that, when executed by the processing circuit, cause the processing circuit to: receive input data regarding a current state of a vehicle; encode the input data to generate encoded input data; supply the encoded input data to a trained statistical model; compute a current context of the vehicle based on the input data using the trained statistical model; compute one or more pilot feedback indicators based on the current context using the trained statistical model; and provide the one or more pilot feedback indicators to a cockpit of the vehicle.

Abstract: Systems, devices, and methods are disclosed for decision making based on plasticity rules of a neural network. A method may include obtaining a multilayered model. The multilayered model may include an input layer including one or more input units. The multilayered model may include one or more hidden layers including one or more hidden units. Each input unit may have a first connection with at least one hidden unit. The multilayered model may include an output layer including one or more output units. The method may also include receiving an input at a first input unit. The method may include sending a first signal from the first input unit to at least one hidden unit via a first connection comprising a first strength. The method may also include making a decision based on the model receiving the input.

Abstract: A pilot support system includes: a processing circuit; and memory storing instructions that, when executed by the processing circuit, cause the processing circuit to: receive input data regarding a current state of a vehicle; encode the input data to generate encoded input data; supply the encoded input data to a trained statistical model; compute a current context of the vehicle based on the input data using the trained statistical model; compute one or more pilot feedback indicators based on the current context using the trained statistical model; and provide the one or more pilot feedback indicators to a cockpit of the vehicle.

Abstract: Systems, devices, and methods are disclosed for decision making based on plasticity rules of a neural network. A method may include obtaining a multilayered model. The multilayered model may include an input layer including one or more input units. The multilayered model may include one or more hidden layers including one or more hidden units. Each input unit may have a first connection with at least one hidden unit. The multilayered model may include an output layer including one or more output units. The method may also include receiving an input at a first input unit. The method may include sending a first signal from the first input unit to at least one hidden unit via a first connection comprising a first strength. The method may also include making a decision based on the model receiving the input.

Abstract: More realistic neural networks are disclosed that are able to learn to solve complex problems though a decision making network, modeled as a virtual entity foraging in a digital environment. Specifically, the neural networks overcome many of the limitations in prior neural networks by using rewarded STDP bounded with rules to solve a complex problem.