[TYPES/announce] Announcing Tactician 1.0 beta

[Lasse Blaauwbroek]

We would like to announce Tactician 1.0 beta1, the first official 
release of Tactician. See the website here 
https://coq-tactician.github.io and an online demo here 
https://coq-tactician.github.io/demo.html

Tactician is a tactic learner and prover for the Coq Proof Assistant. 
The system will help users make tactical proof decisions while they 
retain control over the general proof strategy. To this end, Tactician 
will learn from previously written tactic scripts, and either gives the 
user suggestions about the next tactic to be executed or altogether 
takes over the burden of proof synthesis. Tactician’s goal is to provide 
the user with a seamless, interactive, and intuitive experience together 
with strong, adaptive proof automation.

Even though a lot still remains to be done, with this version we believe 
that the system is mature enough to be used in real developments. We 
would like to solicit any feedback on the system you might have.

Tactician is available for Coq v8.11, v8.12, v8.13 and master and on 
Linux, macOS and Windows. Installation instructions can be found in the 
manual (https://coq-tactician.github.io/manual). Tactician has 
first-class support for Opam (Coq's package manager), and can 
automatically learn from almost any Coq package. For the exceptions, 
special support can be added. Currently, special support exists for the 
HoTT homotopy type theory library. If tactician cannot instrument your 
favorite package and you would like to see support, please open an issue.

-- Future direction --

This release of Tactician is aimed at providing Coq users with an easy 
to use system that can be used in real Coq developments. The next step 
in our grand plan is to transform Tactician into a machine learning 
platform, where AI-researchers can add agents to Tactician (a plugin for 
a plugin) using an easy-to-use API. The goal of this API is to take away 
the hard Coq engineering problems and only leave the hard machine 
learning problems.

This API is still under heavy development. We are therefore not yet 
inviting the wider AI-community to work with Tactician. However, we are 
looking for collaborators/beta-testers. So if you have a good machine 
learning idea that you would like to implement on top of Tactician, 
please get in touch.