Eckity

We are proud to annouce the release of EC-KitY 0.4.0!

This version includes many changes, with the most significant one being **Typed GP**.

What's Changed
* termination_checkers: fixed mistake in comments by ZvikaZ in https://github.com/EC-KitY/EC-KitY/pull/82
* use logging instead of simple 'print's by ZvikaZ in https://github.com/EC-KitY/EC-KitY/pull/66
* add shorter imports by itaitzruia4 in https://github.com/EC-KitY/EC-KitY/pull/99
* fixes in Fitness classes by itaitzruia4 in https://github.com/EC-KitY/EC-KitY/pull/101
* termination_checker: added best_fitness_stagnation_termination_checker by ZvikaZ in https://github.com/EC-KitY/EC-KitY/pull/73
* Fixed typo in functions.py by jack-powers in https://github.com/EC-KitY/EC-KitY/pull/96
* Add update-docs CI/CD by itaitzruia4 in https://github.com/EC-KitY/EC-KitY/pull/107
* MOE: handle corner cases (empty list, zerodivision) by ZvikaZ in https://github.com/EC-KitY/EC-KitY/pull/61
* SubtreeMutation bugfix, run-examples CI/CD, requirements update by itaitzruia4 in https://github.com/EC-KitY/EC-KitY/pull/104
* Update parameter replacement regex by itaitzruia4 in https://github.com/EC-KitY/EC-KitY/pull/108
* Add random detector by achiyae in https://github.com/EC-KitY/EC-KitY/pull/109
* MOE: add statistics/moe_best_worst_statistics.py by ZvikaZ in https://github.com/EC-KitY/EC-KitY/pull/62
* moe: enhance nsga2_plot with axis names and saving by ZvikaZ in https://github.com/EC-KitY/EC-KitY/pull/64
* Add support for Python 3.11 by itaitzruia4 in https://github.com/EC-KitY/EC-KitY/pull/112
* MOEBestWorstStatistics by itaitzruia4 in https://github.com/EC-KitY/EC-KitY/pull/110
* version-detector workflow by itaitzruia4 in https://github.com/EC-KitY/EC-KitY/pull/115
* Add warning for ElitismSelection with zero elites by itaitzruia4 in https://github.com/EC-KitY/EC-KitY/pull/113
* Simple objects no longer iterate over all sub populations by itaitzruia4 in https://github.com/EC-KitY/EC-KitY/pull/105
* Update support for random generator object by itaitzruia4 in https://github.com/EC-KitY/EC-KitY/pull/114
* FP selection, arity validation in Algorithm constructor, no-replacement option in tournament selection by itaitzruia4 in https://github.com/EC-KitY/EC-KitY/pull/116
* `parents` and `update_parents` fields for Individual by itaitzruia4 in https://github.com/EC-KitY/EC-KitY/pull/123
* GA mutations and crossovers docs by itaitzruia4 in https://github.com/EC-KitY/EC-KitY/pull/125
* changed IntVectorOnePointMutation to be more similar to the bit vecto… by eliadsbgu in https://github.com/EC-KitY/EC-KitY/pull/129
* Remove default termination by itaitzruia4 in https://github.com/EC-KitY/EC-KitY/pull/130
* rename MOE classes that contain the word 'test' by itaitzruia4 in https://github.com/EC-KitY/EC-KitY/pull/134
* Typed GP by itaitzruia4 in https://github.com/EC-KitY/EC-KitY/pull/131

New Contributors
* jack-powers made their first contribution in https://github.com/EC-KitY/EC-KitY/pull/96
* eliadsbgu made their first contribution in https://github.com/EC-KitY/EC-KitY/pull/129

**Full Changelog**: https://github.com/EC-KitY/EC-KitY/compare/0.3.4...0.4.0

Several improvements:

- Termination Checker can now also be a list. In that case, early termination is performed if any of the termination conditions apply.
- Generations now range from 1 to max_generation, instead of 0 to max_generation - 1.
Individual now contains informative fields - id, gen, cloned_from, selected_by and applied_operators.
- Vector and its subtypes can now receive a list of the genome (vector cells) as constructor argument.

**ProcessPoolExecutor**
Previously, fitness evaluation tasks could only be submitted to a `ThreadPoolExecutor`.
From now on, the tasks can also be submitted to a `ProcessPoolExecutor` (enhanced performance in some cases).

When initializing an instance of `SimpleEvolution`, use the parameter `executor=process` for a `ProcessPoolExecutor`, or `executor=thread` for a `ThreadPoolExecutor` (the default is value is `thread`).

Multi-Objective Evolution
MOE - multi-objective evolution - from now on you could use EC-KitY to run an evolutionary algorithm with multiple objectives, to receive the Pareto front and find the best solution(s) for you.

IndividualEvaluator.evaluate signature change
`IndividualEvaluator.evaluate` now also receives the entire sub-population individuals, and not only the current individual.
Useful for non-simple cases in which the individual's fitness also depends on the rest of the individuals in its sub-population.

bug fixes for float vector and tests