master
dev
Evolutionary engine for easier hyper-parameter optimization of AI and ML models.
Allow Aipen to be accessed as a web API with a web interface, so that users can provide data and run evolutionary algorithms online without installing anything.
Write the AgentModel, refactor others
Add option for save and load to/from pickled file and JSON/other readable file format.
Should also making serialization better in general.
Previous attempts have broken pip install .
, running into the No module named *
issue.
Fix console_logging=True behavior (locks out other logs).
Implement a source -> channel -> listener system for logging.
Create a 'social-like' side of Aipen, to find the best models for a given problem
Write additional tests for uncovered modules, implement using test cases as a dict key=input, val=expected_ouput. Can have multiple input/outputs.
This task relates to the test coverage tasks and involves setting up the .travis.yml file to integrate with Travis CI and set up any related testing scripts.
Instead of a single log monopolizing the console, we should have an option for logs to open consoles in other windows which listen to them (e.g. an arena console window, an evaluation console window, ...)
Document original, undocumented code in the repo's GitHub wiki.
Write some basic visualization processes using an appropriate third party library. Should be as decoupled from third party library as possible so we can switch to another if needed.
Bugs:
E.g. by using a matrix
Test that log functionality works by expected, can use a special log channel
Should conform with system being developed in #5
The line !**.gitkeep
in .gitignore
does not serve to maintain empty folders (e.g. the logging folder), so either this should be fixed or else a utils
file should be created to manage path and file creation.
Various bits of code, especially in the arena code should be clean up and refactored, renaming as required and breaking apart functionality.
Following up to #8, add processing functions such as padding, noise reduction, transforms, etc as they are needed
Be wary of import errors with some directory structures: https://stackoverflow.com/a/50559323/7195043
Management of data storage and ids
Should interface with visualization module and use numpy types as underlying data storage
Look at a testing system which checks for test coverage and emits warnings when test coverage is low in a commit.
Write a data generation module capable of generating simple bits of data, e.g. random, linear with noise
Either improve or remove the abstract classes and methods.
Add dict/function/etc for parameters (for learning) and hyper-parameters (for evolution) to models. Allows learning optimizers and evolutionary engine to spawn models better than random.
Implement MLProblem and AgentProblem (and come up with a better name if you can) plus at least one implementation of each, based on a toy problem.
Consider making SupervisedProblem and UnsupervisedProblem interfaces with slightly difference APIs.
Recommend implementing noisy linear data fitting for MLProblem and Battleship for AgentProblem.
Allow the Aipen arena to optimize instance of itself.
Follow up to initial data generation module, grabbing data from actual sources/problems/etc
Should include an id system, even if it's just an initial implementation. Could use in-memory sqlite3.
OpenAI gyms, image recognition, etc
Optimize evolutionary learning and intra-round learning.
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