We need to simulate problems where human solutions deviate from what is observably optimal. With AI, the program must model both the underlying physics of a problem, and it must model a human response to this physical model.
For both of these models we must decide how much detail to build in.
These models include rules that often resemble or approximate equations from quantum mechanics. A particularly interesting similarity is the statistical nature of Bayesian calculations and the statistical representation of amplitude flows in quantum mechanics.
Shane,
We need to simulate problems where human solutions deviate from what is observably optimal. With AI, the program must model both the underlying physics of a problem, and it must model a human response to this physical model.
For both of these models we must decide how much detail to build in.
These models include rules that often resemble or approximate equations from quantum mechanics. A particularly interesting similarity is the statistical nature of Bayesian calculations and the statistical representation of amplitude flows in quantum mechanics.