(Or “HTML and JavaScript for Web 3.0 all-in-one”.)
Thank you all for the ardent interest in a language which is not fully stable yet. Escher is expected to be stable in 2015. Until then the documentation below will likely be out of date, but generally informative. I am doing my best to build the first end-to-end (end-user to datacenter) Escher app: A live cluster orchestration tool.
Escher is a programming language for everything. It can naturally represent both process and data, while being simpler than a calculator grammar.
Escher is a language for building intelligent real-time translations between the semantics of different physical devices accessible through chains or networks of digital or electrical technologies.
In Escher, you can program from first- and third-person point-of-view at the same time. (Just like Physics is particles and waves at the same time.)
Some of the application domains of Escher are:
- Definition and generation of synthetic worlds governed by Physical laws, as in Augmented Reality and the Gaming Industry,
- General purpose concurrent and distributed programming, such as Internet services and cloud applications,
- Relational data representation, as in databases and CAD file formats,
- Real-time control loops, as in Robotics,
- Numerical and scientific computation pipelines,
- Anything that filters information from some input sources, in real-time, and sends a transformed form to output devices!
An early “proposal” for the design of Escher, Escher: A black-and-white language for data and process representation, might be an informative (but not necessary) read for the theoretically inclined.
The Escher abstraction of the world is NOT Turing-compatible: From the point-of-view of an Escher program, there is no input and output: There are only emergences and disappearances of events.
Escher presents the world in a model called Choiceless Computation, introduced by the legendary Mathematicians Andreas Blass, Yuri Gurevich and Saharon Shelah, and introduced to me by the dare-to-be-great, soon-to-be-legendary, although-already-should-be Benjamin Rossman.
Understanding the difference between Turing Machines and Choiceless Computation, while not entirely necessary, sheds much light on the profound difference between Escher and other languages. The relevant publications are quoted in the bibliography at the end.
The following puzzle demonstrates choiceless programming via a simple relatable high-school Math puzzle:
Four beer caps are placed on the corners of a square table with arbitrary orientations. There is a robot on the table that acts upon three commands: (a) “flip a corner cap”, (b) “flip two diagonal caps” and (c) “flip two caps along a side”
Upon action there is no guarantee as to which corner, diagonal or side, respectively, the robot will choose to flip.
Devise a sequence of commands that forces the robot to turn all caps in a configuration where they all have the same orientation.
Can you devise a sequence that ensures they all face up? Down?
I was introduced to the notion of choiceless programming via this puzzle by Benjamin Rossman.
Escher is an interpreter, comprising a singular executable binary. It can be built for Linux, Darwin and Windows.
Given that the Go Language compiler is installed, you can build and install the circuit binary with one line:
go get github.com/gocircuit/escher/escher
Go to the Escher base directory and run one of the tutorials
escher -src tutorial/helloworld
An Escher program is a collection of interconnected reflexes. A reflex, the only abstraction in Escher, represents an independent computing entity that can interact with the “outside world” through a collection of named valves.
The illustration below shows a reflex, named AND, which has three valves,
named X, Y and XandY, respectively.
A reflex can be implemented in another technology (currently only the Go Programming Language is supported as an external technology) or it can be composed of pre-existing reflexes. The former is called a gate, while the latter is called a circuit.
Gates are reflexes whose behvaior is implemented in a the underlying technology, which is the Go language, at the moment. From Escher's point-of-view (POV), gates are simply reflexes that broker values. But from the user's POV, gates can have “side-effects” in the “outside world” and, vice-versa, the outside world can prompt reflexive action, such as sending out a message over a valve asynchronously.
To implement your own gates, take example from the implementation of the “reasoning” gate (discussed later).
Circuits are a composition of a few reflexes.
Programmatically, this circuit is defined by the code:
nand {
// reflex recollections
and and
not not
// connections
not.X = and.XandY
XnandY = not.notX
and.X = X
and.Y = Y
}
Escher programs are designated by a local root directory and all its descendants. That directory is represented as the root in the faculty namespace inside the Escher programming environment.
Escher compiles all files ending in .escher and attaches the resulting circuit designs
to the namespaces corresponding to their directory parents.
To materialize (i.e. run) an Escher program, use the mandatory -x flag to specify the path to the local
source directory.
escher -x tutorial/helloworld
Escher materializes the circuit design named main in the root source directory, e.g.
// The main circuit is always the one materialized (executed).
main {
s @show
s.Action = "¡Hello, world!"
}
To facilitate different embodiments (aka implementations) of gate functionalities, Escher allows the mixing of two source hierarchies into a single execution.
For instance, the hierarchy acid/karajan contains circuit definitions (in terms
of gates or other circuits), while the hierarchy tutorial/circuit/autorespawn
contains a root main circuit. To execution the latter, using the former as
a “library” available in the visisble namespace, run for instance
escher \
-x tutorial/circuit/autorespawn \
-y acid/karajan \
-n ExecutionName \
-s Server=Xa3242440007ad57b \
-d 228.8.8.8:22
By default, the Escher environment provides a basic set of gates (a basis), which enable a rich (infinite) language of possibilities in data manipulation.
Collectively, they are data (concept) and transformation (sentence) gates
These gates are not part of Escher's semantics. They are merely an optional library—a playground for beginners. Users can implement their own gates for data and transformation.
The basis reference below is nearly entirely visual. You will notice that the visual language follows a prescribed format.
On blank slate, there is “nothing to do”—so to speak. For this reason, we have a collection of gates which are effectively “springs” of objects.
Some produce integers, some floats, some complex numbers, some strings. These are familiar types.
There is one gate that produces “trees”. Trees are the basic type of “weavable” (or mutable) knowledge. (In fact, the other types are not necessary but we throw them in for convenience.)
In the illustration below, the syntax of the respective gate design is displayed as their name (white on black).
Arithmetic gates are a sufficient basis of operations that enables algorithmic manipulation of the types string, int, float and complex. Coming soon.
You will notice, one of the basic data gates allows the creation of a struct-like object. This is called a tree. It is a novel data structure, described in detail in “Extensible records with scoped labels” by Daan Leijen.
These data structures are “built out” and “trimmed down” using three elegant reflection methods, described in the above publication.
Escher embodies all three in one gate, whose main purpose is to manipulate the contents of trees. This is the Reason Gate, illustrated below.
The following three illustrations show the same gate design, but under different orientations of the event streams. In all valid cases, the relationship between the valve values shown examplifies the effect of the gate.
Belief for the current state of the world, combined with a new observation, results in a theory.
A theory of observations, which explains (includes) an observation at hand, explains the observation only to a belief consisting of the theory without the observation.
When a belief of the state of the world is combined with a theory that is bigger, the conjectured difference must be found in a new observation.
Duality gates are the boundary between Escher semantics and the outside world. They are the I/O with the outside. Such gates affect some external technology when prompted through Escher in a certain way. Alternatively, such gates might fire an Escher message on one of its valves, in response to an asynchronous events occuring in an external technology.
For instance, with the gates we've seen so far, one might construct the following higher-level circuit abstraction for an I/O device, which is controlled by a defered logic:
And the respective source code:
io_device {
// recalls
in see
out show
swtch switch
// matchings
Logic = swtch.Socialize
in.Sensation = swtch.Hear
out.Action = swtch.Speak
}
This special type of gates fulfills the complementary functions of constructing new circuit designs “dynamically” (akin to “reflection” in other languages), and materializing (i.e. executing) these designs. Coming soon.
Coming soon.
Coming soon.
I envision that in the natural course of action at play, … (more coming soon).
It may seem that Escher is not more than a new semantic to do an old job. But something nearly magical happens when transition to using the Escher semantic—various compiler intelligence improvements that used to be NP-hard become simple and tractable:
-
Users do not need to explicitly moduralize (sub-divide) their circuits. One could start designing a circuit wiring and the compiler will automatically find sub-patterns that are abstractable as circuits. Which includes non-obvious and/or recursive ones.
-
Code speed/space/etc optimizations reduce to a simple sub-graph replacement game, highly transparent to and customizable by the user.
…if you think this language is #KingOfMetaphor, please, tweet to
@StephenAtHome that his title of
#KingOfMetaphor is being challenged, in a good way. Tweet
that @escherio wants a #ColbertBump. The #ColbertFaculty is coming soon.
…if you want to inquire about the science behind @escherio, tweet to me, Petar @maymounkov.
Or, simply lose yourself in the initial thoughts that led to the invention of Escher.
To me, Escher is a language for weaving dreams: It makes imagination real. Help me make it tangible, so it can be shared.
- DARPA XDATA initiative under the program management of Dr. Christopher White, 2013–2014
- Data Tactics Corp, 2013–2014
- L3, 2014
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Choiceless Polynomial Time, Andreas Blass, Yuri Gurevich and Saharon Shelah, published by Shelah Office on arXiv, 1997
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Choiceless Polynomial Time Logic: Inability to Express, Saharon Shelah, Springer Lecture Notes in Computer Science, Volume 1862, 2000, pp. 72-125
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Circuits of the Mind, Leslie Valiant, 2000
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Probably Approximately Correct, 53589083, Leslie Valiant, 2013
Additional, enlightening reading includes:
- Ancient Evenings, Norman Mailer, 1983
- Yoga Philosophy of Patañjali, State University of New York Press, 1984
- Samskrta-Subodhini: A Sanskrit Primer, Michigan Papers on South and Southeast Asia, Book 47, 1999
People working in this or unsuspectingly related areas:
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Steven Witten and Kyle McDonald for heroic attempts at fluidity in digital art.
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Bret Victor for the insight that inventing a good user interface and reverse-engineering the mind is one and the same thing.
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Noam Chomsky for suggesting that discrepancies in language vs action are a window into the producing device, as well as the circularity of the meaning of languages.
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John Conway for the Symmetries of Things.
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Daniel Spielman for the insight that general linear systems will never be invertible in linear time, because there are no naturally linguistically-posable problems that can result in such matrices. As well as the insight that even circular objects (like general undirected graphs) have to be intellectually broken down to “simple” trees (via the notion of “distribution of trees”) in order to enable a thinking process: Thereby motivting the “tree of knowledge” data representation.
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Madhu Sudan and Irit Dinur for Probabilistically-checkable Proofs and Universal Semantic Communication.
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Steven Boyd for pointing my attention to the relationship between convex optimization CVX and language.
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Leslie Valiant for Circuits of the Mind and Probably Approximately Correct, as well as for inspiring a spirit of thought outside of my profession (Theoretical Computer Science).
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Saharon Shelah for the notion of Choiceless Computation.
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William Thurston for the Geometry and Topology of Three-manifolds.
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Ken Thompson and Rob Pike for their pioneering work in programming languages that enabled the idea and later, via the Go Language, the realization of Escher.
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Ken Stephenson and his work on Circle Packings
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The Clay Institute for the insight that reducing the count of open problems and the theoretical unification of logical theories (reducing the count of axioms) are one and the same thing.
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And much more.