Good cellular automaton for evolving life?

How has life in our universe arisen? I think basically there was a box of sand and it was shook until robust replicating structures emerged.

One could try to do the same thing with Conway’s game of life, but most of its structures are extremely fragile. A different automaton might be better suited. Maybe one where objects can emerge and travel and persist more easily. Suggestions?

I would want to randomly initialize a large starting state and run it (with noise injection) for a long time and see what kinds of structures emerge.

Evolving conversions between trees (representing JSON) and graphs (representing relational database schemas)

I have in input different, say 100, types of trees with labeled nodes (representing JSON files). I need to transform the information contained in the trees into graphs with labeled nodes (representing insert statements into tables in a relational database).

The structure of the trees evolves very quickly. Every month some labels are moved, renamed, or their type changes.

Let’s say that I know how to transform trees into graphs at time t, is is possible to infer somehow at least part of the new transformations with the new tree structure?

Are there papers or books that I need to read to know some theory that could help me to tackle this task?

Paging operations research people: how is the field evolving? [on hold]

I asked this question to the OR community ( but, since there are quite a few CS people working in OR, I would like to get the perspective of the community.

Classically, it seems the problems that OR people studied (at least the ones I am most familiar with) were related to decision theory, optimization and scheduling, and queuing theory with the general sentiment that solving these problems would be of interest to a company’s operations.

More recently, the lines between OR and other fields have gotten a bit more blurry for me. I am seeing more venues that focus on the intersection between OR, economics (game theory), and computer science. For example, see the recent talks at EC. Also see a new INFORMS conference on the intersection of OR and security.

Question(s): My main question concerns the current trajectory of the OR field and OR departments. Is the focus of OR becoming blurry or has the underlying motivation for the field changed? What’s the future for OR: as problems traditionally studied under OR become more central in society, will other fields (e.g. computer science) begin to take over/cannibalize OR departments?

Evolving expert systems with machine learning

Expert systems seem to have been left at the wayside a little bit in the 21st century. In fact, expert-systems was not even a tag on this site (until I just created it). The traditional focus in expert systems has been on rule based systems and logical resolution via, for example, 2-SAT backward chaining. Have there been attempts to integrate modern machine learning with traditional expert systems theory?