1. A computer-implemented method for recognizing an event pattern for objects that belong to an event domain, the method comprising: activating a pattern query that corresponds to the event pattern and that has at least one state with a distinctive transition probability to reach a final query state, said distinctive transition probability representing a lower transition probability of said at least one state to reach said final state, said lower probability is lower compared to at least one other transition probability to reach said final state of at least one second state, other than said at least one state, the probability being derived from object observations in the event domain; wherein an instance reaching said distinctive transition probability state uses a longer time interval than an instance not reaching said distinctive transition probability state; continuously receiving event representations, that are related to the objects; allocating the event representations to a first processing resource to initiate instances of the query; monitoring the instances and, upon receiving event representations that cause an instance of said instances to reach the state with the distinctive transition probability, shifting the instance to a second processing resource that is more optimized for handling longer time interval than said first processing resource.