Computer-implemented method for assisting operation of an agent operating in a dynamic environment involving at least one other agent in the environment of the agent, wherein the method comprises acquiring sensor data from at least one sensor physically sensing the environment, including information on the at least one other agent and on physical structures in the environment; acquiring data, from at least one ego-sensor, including information on position and motion of the agent, wherein the information on position and motion includes information on a position, a heading, a velocity and an acceleration or deceleration of the ego-agent; calculating an importance score for each agent of the at least one other agent based on the acquired sensor data and the acquired information on position and motion, wherein the importance score is a quantitative physical value describing a relevance of the particular agent for the operated agent based on the acquired sensor data and the acquired information on position and motion; generating a list comprising the at least one other agent based on the calculated importance scores of the at least one other agent, partitioning the generated list in at least one partition based on the importance score of the at least one other agent, wherein each partition includes at least one other agent; generating a prediction result by predicting a behavior of the at least one agent included in the at least one partition based on the sensor data and the position and motion information using a selected behavior prediction model, wherein the selected behavior prediction model is selected from a plurality of behavior prediction models based on the importance score of the at least one agent included in the at least one partition; outputting the prediction result to a planning and/or control system for operating the agent or for generating and outputting an information signal or warning signal via a human machine interface; and characterized in that calculating the importance score comprises applying a risk shadowing process to the data on the at least one other agent and on the physical structures in the environment, wherein the risk shadowing process comprises performing a reachability analysis based on the sensor data and the position and motion information for determining occupied areas for the agent and the at least one other agent in the environment over time, determining overlapping areas from the occupied areas of the agent and the at least one other agent, and determining a relevance of each of the at least one other agent based on the determined overlapping areas. acquiring sensor data from at least one sensor physically sensing the environment, including information on the at least one other agent and on physical structures in the environment; acquiring data, from at least one ego-sensor, including information on position and motion of the agent, wherein the information on position and motion includes information on a position, a heading, a velocity and an acceleration or deceleration of the ego-agent; calculating an importance score for each agent of the at least one other agent based on the acquired sensor data and the acquired information on position and motion, wherein the importance score is a quantitative physical value describing a relevance of the particular agent for the operated agent based on the acquired sensor data and the acquired information on position and motion; generating a list comprising the at least one other agent based on the calculated importance scores of the at least one other agent, partitioning the generated list in at least one partition based on the importance score of the at least one other agent, wherein each partition includes at least one other agent; generating a prediction result by predicting a behavior of the at least one agent included in the at least one partition based on the sensor data and the position and motion information using a selected behavior prediction model, wherein the selected behavior prediction model is selected from a plurality of behavior prediction models based on the importance score of the at least one agent included in the at least one partition; outputting the prediction result to a planning and/or control system for operating the agent or for generating and outputting an information signal or warning signal via a human machine interface; and characterized in that calculating the importance score comprises applying a risk shadowing process to the data on the at least one other agent and on the physical structures in the environment, wherein the risk shadowing process comprises performing a reachability analysis based on the sensor data and the position and motion information for determining occupied areas for the agent and the at least one other agent in the environment over time, determining overlapping areas from the occupied areas of the agent and the at least one other agent, and determining a relevance of each of the at least one other agent based on the determined overlapping areas.