Thomas Cover did a great many interesting things. His work on universal data compression and the universal portfolio could provide very efficient and useful optimization approaches for use in AI & AGI.
Cover’s universal optimization approaches grow out of the beginnings of information theory, especially John Kelly’s work at Bell Labs in the 1950s.
In his "universal" approaches, Cover developed the theoretical optimization framework for identifying, at successive time steps, the mean rank-weighting “portfolio” of agents/algorithms/performace from an infinite number of possible combinations of the inputs.
Think of this as a multi-dimensional regular simplex with rank weightings as a hyper-cap. One can then find the mean rank-weighted “portfolio” geometrically.
Cover proved that successively following... (read more)
Thomas Cover did a great many interesting things. His work on universal data compression and the universal portfolio could provide very efficient and useful optimization approaches for use in AI & AGI.
Cover’s universal optimization approaches grow out of the beginnings of information theory, especially John Kelly’s work at Bell Labs in the 1950s.
In his "universal" approaches, Cover developed the theoretical optimization framework for identifying, at successive time steps, the mean rank-weighting “portfolio” of agents/algorithms/performace from an infinite number of possible combinations of the inputs.
Think of this as a multi-dimensional regular simplex with rank weightings as a hyper-cap. One can then find the mean rank-weighted “portfolio” geometrically.
Cover proved that successively following... (read more)