By asking 306 subjects to pick which of six colors they felt was the true red, light green, blue, yellow, or purple, researchers built probability distributions for each color. They then used Kullback-Leibler divergence to measure the difference between the reference color's distribution and that of each generated color. The number of subjects who selected a generated color decreased as its Kullback-Leibler divergence from the reference increased, but the rate of decrease varied greatly across colors. This suggests that color qualia—the subjective sensation of a color—are not uniform across hues; people appear to randomly choose a color that 'feels' right.
A previously proposed mathematical model of consciousness, the HLbC model, is applied to psychological phenomena and shown to account for optical illusions, empathy, mutual understanding, and prospect theory. Optical illusions like Rubin's vase arise from stochastic fluctuations in consciousness when a figure permits multiple interpretations. Empathy and mutual understanding are mathematically represented using Kullback-Leibler divergence, a core component of the model. The model also successfully explains properties of prospect theory, which underlies behavioral economics. These results indicate the HLbC model can explain aspects of psychological consciousness.
A mathematical model of consciousness and will is proposed. First, a toy neural network simulated inverted qualia, confirming that qualia are individual-dependent and thus difficult to use as an indicator of consciousness and will. To address this, a probability space and a random variable are introduced into a set of qualia, defining a human language for events. Consciousness and will are then modeled: future actions are randomly selected from a comparison between external event recognition and past episodic memory, and the actual recognition of actions is regarded as the occurrence of consciousness. The basic formula is derived and compared with past philosophical discussions.
A mathematical model of consciousness and will is proposed, starting with a neural-network simulation that confirms inverted qualia—subjective experiences that differ between individuals, making qualia unreliable as indicators of consciousness. To address this, a probability space and random variable are introduced over a set of qualia, defining a public language for events. Consciousness and will are modeled as future actions randomly selected from a comparison between external event recognition and past episodic memory, with actual action recognition constituting the occurrence of consciousness. A basic formula is derived, and the proposal is compared with prior philosophical discussions.