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A theoretical model for deriving the origin of emotional functions from first principles is introduced. The model, called "Emotional Model Of the Theoretical Interpretations Of Neuroprocessing", abbreviated as the "EMO- TION", derives how emotional context can be evolved from innate responses. It is based on a biological framework for autonomous systems with minimal assumptions on the system or what emotion is. The first phase of the model (EMO- TION-I) addresses the progressive abstraction of the sensory input signals within relevant context of the environment to produce the appropriate output actions for survival. It uses a probabilistic feedforward and feedback neural network with multiple adaptable gains, self-adaptive learning rate and modifiable connection weights to produce a self-organizing, self- adaptive system incorporating associative reinforcement learning rules for conditioning and fixation of circuitry into hardwire to form innate responses such that contextual feel of sensation is evolved as an emergent property known as emotional feel.

EMOTION-I Model: A Biologically-Based Theoretical Framework for Deriving Emotional Context of Sensation in Autonomous Control Systems