Sure, datalisp is really a very simple idea. First we take canonical S-expressions (made by Ron Rivest for cryptographic signing) as the syntax of the "languag

Sure, datalisp is really a very simple idea. First we take canonical S-expressions (made by Ron Rivest for cryptographic signing) as the syntax of the "language" (again it's primarily a data-interchange format meant to be used to build distributed systems). We enforce the restriction that the csexps must have versioned operators, that is (2:op1:0...) would be a the operation `op` and version `0`, the version is a natural number. That's it for the data interchange format, now for the semantics of the language. As I have been saying the primary idea is to use propagator networks (propnets). The name of datalisp comes from datafun which is an extension of datalog. Datalog is something you are probably familiar with, it's not turing complete and is a constructive logic programming language that uses "relations" and postulated "facts" to infer new "facts" - i.e. it builds out a transitive closure of sorts. Datafun takes this and tries to extend it as much as possible without becoming turing complete, so rather than being limited to the boolean lattice of normal logic it uses any lattice and monotone functions, e.g. a propnet. However it tries to do type inference and be a "programming language". One nice property of datalog is that the evaluation semantics coincide with the shortest vector path algorithm used to do routing on the internet, except datalog is declerative rather than imperative so it's an interesting way to do routing. The idea of datalisp is to make the "XPath of canonical S-expressions" be a datafun-ish language that can then also do the routing. Now the reason this has anything to do with cryptocurrencies is based on the claim that the internet is a propnet where each place is a "max-signal lattice". The idea being that each user tries to put the computer into a state that most aligns with their intent (`max` over a total order - in this case ordered by "signal" - is a lattice), therefore they will not choose to persist messages that are spam i.e. messaging in the network is monotone (at the limit you have security and only choose to replace information if it rewards you with higher signal). The goal of the datalisp network is to make this intuition concrete. There is a lot of details but this is the general gist. So the anti-sybil mechanism in the network is called "proof of trust" we make participants in the network sign their messages and include a prediction of the signal-vs-noise of their message. Peers in the network will have a prior how much to trust the self-evaluation of this key that they then use to order the message. Second order byzantine fault tolerance is a class of problems and the representative problem we try to solve (i.e. a "second order decentralization complete problem") is deciding whether to merge a patch and rebuild your system in a byzantine setting. If you can do that then you can of course also do a ledger that simulates some formal language. This is a fancy way to say we want a way to do updates in a distributed system with no single source of truth. The consensus mechanism is based in lattice theory, we have "join consensus" which is a race of sorts, that is you can always merge a patch ahead of the network if you like (stay on the "bleeding edge" so to speak) and then there is a "meet consensus" which is based on the avalanche algorithm and is used to move up the bottom and collapse all patches (or more generally; metadata) into its state. So the semantics of datalisp end up being something similar to "probabilistic datafun" if you are familiar with semi-naive datalog evaluation semantics then it's a bit like that except we also have a cutoff w.r.t. how much confidence we are willing to tolerate to use a fact / inference. Instead of programming datalisp in a text editor it is more like a graphql of sorts, it /is/ the internet, or rather it reifies the propnet datastructure. The reason we care so much about canonicality and consensus is so that we can take advantage of content addressing. I have some ideas about building on top of this framework mixnets and simulations of different political systems, then the idea is to do composition via constant function market makers since they are convex and therefore solve the tragedy of the commons (local optimization is global optimization). Since the network is decentralized you can be byzantine, that is you can make your own identifiers in datalisp (each operator has an infinite namespace due to versioning, we use the probabilistic logic programming and metadata gossiping in the network to find out what schema the data is supposed to fit, if there is a namespace clash we form a local consensus to re-version one of the clashing names to the first unused version). The properties of lattices allow you to "zoom out" of such echo chamber bickering.. this is how anti-sybil works... There's a lot of ideas basically, I hope you can see the general picture of what I am planning.