In general some familiarity is assumed. Multi-scale descriptions are needed to understand complex systems. Fine scales influence large scale behavior. The specific methods of deterministic chaos are not exclusive of more general issue of fine scale effects on large scale behavior. Dynamics on such a landscape do not average simply.
Attractor networks use local minima as memories.
There is much discussion of this question. The amount of information necessary to describe the system. There are various important issues that require clarification. One of these relates to the use of inference to obtain the description from a seemingly smaller amount of information. This leads the concept of algorithmic complexity.