Communities and police face numeruous ever-changing challenges in 
fighting crime. By sharing and learning from other cities experience, 
police/community partnerships will be better able to successfully 
deal with these challenges. In this project, advanced algorithms from
computer science research in Case-based Reasoning (CBR) are used 
to identify for police officials and citizens similar communities in 
terms of economics, crime, police resources, etc., helping them develop
colleague networks. 
	Increased support of information flow among police departments 
will help them learn from each others experiences, leading to: 
1. provide a pool of innovative strategies; 2. help to avoid previous 
failures; 3. make proactive measures more likely by helping officials 
to anticipate new problems and trends; and 4. encourage strategic, 
long-range thinking and planning, rather than mere tactical planning.