A micro-world is described, in which many analogies involving strikingly different concepts and levels of subtlety can be made. The question "What differentiates the good ones from the bad ones?" is discussed, and then the problem of how to implement a computational model of the human ability to come up with such analogies (and to have a sense for their quality) is considered. A key part of the proposed system, now under development is its dependence on statistically emergent properties of stochastically interacting "codelets" (small pieces of ready-to-run code created by the system, and selected at random to run with probability proportional to heuristically assigned "urgencies"). Another key element is a network of linked concepts of varying levels of "semanticity", in which activation spreads and indirectly controls the urgencies of new codelets. There is pressure in the system toward maximizing the degree of "semanticity" or "intensionality" of descriptions of structures, but many such pressures, often conflicting, must interact with one another, and compromises must be made. The shifting of (1) perceived oundaries inside structures, (2) descriptive concepts chosen to apply to structures, and (3) features perceived as "salient" or not, is called "slippage". What can slip, and how are emergent consequences of the interaction of (1) the temporary ("cytoplasmic") structures involved in the analogy with (2) the permanent ("Platonic") concepts and links in the conceptual proximity network, or "slippability network". The architecture of this system is postulated as a general architecture suitable for dealing not only with fluid analogies, but also with other types of abstract perception and categorization tasks, such as musical perception, scientific theorizing, Bongard problems and others.