Given a set of agents with valid previous knowledge bases, we wish to know how new knowledge affects each agent. To model the new knowledge, boolean logic is used, expressed by 2CNF clauses, to reduce the complexity. Upon recieving new knowledge, one or more agents may find it inconsistent with their previous knowledge base, so a mechanism is applied which removes knowledge by using a contraction operation, described by the AGM model. The goal is to determinate if that contradicting knowledge significantly affects the set of beliefs of each agent. Further more, a problem is modeled in which, given a set of agents and their knowledge base, some clauses representing new knowledge are added with the aim of determining which agent is the most affected, due to contradiction with the previous knowledge.