Metadata-Version: 1.1
Name: LSpackage
Version: 0.1
Summary: An implementation of Local Search algorithms based on single solution design
Home-page: http://github.com/alexandur/LSpackage
Author: Andurnache Alexandru
Author-email: alex.andur@yahoo.com
License: LICENSE.txt
Description: 
        Local Search - Metaheuristic
        ============================
        
        Project GIT address: https://github.com/anduralex/LSpackage.git
        
        This lib implements some algorithms described on the book "Metaheuristics - From Design to Implementation", from El-Ghazali Talbi.
        
        This implementation takes some of the ideas from the SimpleAI implementation. I am testing the majority of the lib, it's available via pip install, has a standard repo and lib architecture, well documented.
        
        At this moment, the implementation includes:
        
        * Search
            * Local Search algorithms
        
        Installation
        ============
        
        Just get it:
        
        .. code-block:: none
        
            pip install LSpackage
        
        You will need to have pip installed on your system. On linux install the 
        python-pip package.
        
        Examples
        ========
        
        LSpackage allows you to define problems and look for the solution with
        different strategies. Another samples are in the ``samples`` directory, but
        here is an easy one.
        
        This problem tries to create the string "HELLO WORLD" using _local_search algorithm:
        
        .. code-block:: python
        
         from code.models import SearchProblem
         from code.local import hill_climbing,_local_search,_first_expander
         GOAL ='HELLO WORLD'
        
         class HelloProblem(SearchProblem):
            def actions(self, state):
                if len(state) < len(GOAL):
                    return list(' ABCDEFGHIJKLMNOPQRSTUVWXYZ')
                else:
                    return []
        
            def result(self, state, action):
                return state+action
        
            def value(self, state):
                return sum(1 if state[i] == GOAL[i] else 0
                           for i in range(min(len(GOAL), len(state))))
        
          problem = HelloProblem(initial_state='')
          result = _local_search(problem, _first_expander)
          print(result.state)
        
        More detailed documentation
        ===========================
        
        You can read the book "Metaheuristics - From Design to Implementation", from El-Ghazali Talbi. Or for offline access, you can clone the project code repository and work with it.
            
        Authors
        =======
        
        * Andurnache Alexandru
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
