and is provided with g s corresponding to g at the
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” where “complexity” is gauged by the assumed measures ν and γ.
and γ is defined to weight goals according to
and this bias is appropriately reflected
and mostly go about their lives doing things
and a subspace ∆ ∈ Σ µ of inference agents
using the languages of category theory and information geometry.
but then refined by inference and other processes). The assumed intelligent agent
each of which is associated with specific algorithms and structures
and the PLN uncertain inference framework (see Chapter 34). The
and be unsolvable by any system not far along
and they’re also of practical importance when one
the extreme commonality of symmetry groups in the (everyday and
and another agent is able to interpret the meaning
that does not fall into any of these categories and constitutes “mixed knowledge.”