I don’t know where you got the part about representational equilibria from.
My conception of a monad is that it is “physically elementary” but can have “mental states”. Mental states are complex so there’s some sort of structure there, but it’s not spatial structure. The monad isn’t obtained by physically concatenating simpler objects; its complexity has some other nature.
Consider the Game of Life cellular automaton. The cells are the “physically elementary objects” and they can have one of two states, “on” or “off”.
Now imagine a cellular automaton in which the state space of each individual cell is a set of binary trees of arbitrary depth. So the sequence of states experienced by a single cell, rather than being like 0, 1, 1, 0, 0, 0,… might be more like (X(XX)), (XX), ((XX)X), (X(XX)), (X(X(XX)))… There’s an internal combinatorial structure to the state of the single entity, and ontologically some of these states might even be phenomenal or intentional states.
Finally, if you get this dynamics as a result of something like the changing tensor decomposition of one of those quantum CAs, then you would have a causal system which mathematically is an automaton of “tree-state” cells, ontologically is a causal grid of monads capable of developing internal intentionality, and physically is described by a Hamiltonian built out of Pauli matrices, such as might describe a many-body quantum system.
Furthermore, since the states of the individual cell can have great or even arbitrary internal complexity, it may be possible to simulate the dynamics of a single grid-cell in complex states, using a large number of grid-cells in simple states. The simulated complex tree-states would actually be a concatenation of simple tree-states. This is the “network of a billion simple monads simulating a single complex monad”.
I don’t know where you got the part about representational equilibria from.
My conception of a monad is that it is “physically elementary” but can have “mental states”. Mental states are complex so there’s some sort of structure there, but it’s not spatial structure. The monad isn’t obtained by physically concatenating simpler objects; its complexity has some other nature.
Consider the Game of Life cellular automaton. The cells are the “physically elementary objects” and they can have one of two states, “on” or “off”.
Now imagine a cellular automaton in which the state space of each individual cell is a set of binary trees of arbitrary depth. So the sequence of states experienced by a single cell, rather than being like 0, 1, 1, 0, 0, 0,… might be more like (X(XX)), (XX), ((XX)X), (X(XX)), (X(X(XX)))… There’s an internal combinatorial structure to the state of the single entity, and ontologically some of these states might even be phenomenal or intentional states.
Finally, if you get this dynamics as a result of something like the changing tensor decomposition of one of those quantum CAs, then you would have a causal system which mathematically is an automaton of “tree-state” cells, ontologically is a causal grid of monads capable of developing internal intentionality, and physically is described by a Hamiltonian built out of Pauli matrices, such as might describe a many-body quantum system.
Furthermore, since the states of the individual cell can have great or even arbitrary internal complexity, it may be possible to simulate the dynamics of a single grid-cell in complex states, using a large number of grid-cells in simple states. The simulated complex tree-states would actually be a concatenation of simple tree-states. This is the “network of a billion simple monads simulating a single complex monad”.