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@@ -7,9 +7,9 @@ Modules description
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**Macop** offers the following main and basic features:
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- **algorithms:** generic and implemented optimisation research algorithms;
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-- **callbacks:** callbacks to automatically keep track of the search space advancement;
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+- **callbacks:** callbacks to automatically keep track of the search space advancement and restart from previous state if nedded;
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- **evaluator:** stores problem instance data and implement a `compute` method in order to evaluate a solution;
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-- **operators:** mutators, crossovers update of solution;
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+- **operators:** mutators, crossovers operators for update and obtain new solution;
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- **policies:** the way you choose the available operators (might be using reinforcement learning);
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- **solutions:** representation of the solution;
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- **validator:** such as constraint programmig, a `validator` is function which is used for validate or not a solution data state.
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