To identify a scenario that will bear a good simulation result from among a plurality of scenarios used in an agent-based simulation with a reduced amount of computation, there is provided an information processing apparatus comprising a counting part configured to count the number of agents in each of a plurality of states at a middle of a simulation that involves a plurality of agents, and a generation part configured to generate characteristic data used for prediction of a result of the simulation based on the number of agents in each of the plurality of states.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. An information processing apparatus, comprising: a counting part configured to count the number of agents in each of a plurality of states at a middle of a simulation that involves a plurality of agents; and a generation part configured to generate characteristic data used for prediction of a result of the simulation based on the number of agents in each of the plurality of states. 2. The information processing apparatus according to claim 1, further comprising: a prediction part configured to predict whether the simulation result is good or bad based on the characteristic data. 3. The information processing apparatus according to claim 2, further comprising: a simulation part configured to perform the simulation under a plurality of simulation conditions; and a learning part configured to allow the prediction part to learn from a plurality of pieces of characteristic data generated in the middle of the simulations under the respective simulation conditions and a plurality of corresponding simulation results. 4. The information processing apparatus according to claim 3, further comprising: an interruption part configured to interrupt the simulation in response to a prediction that the result of the simulation is bad. 5. The information processing apparatus according to claim 4, wherein the interruption part changes a level for interruption of a simulation based on a predefined number of top-ranked evaluations of a plurality of evaluations obtained by completing the simulations under the plurality of simulation conditions. 6. The information processing apparatus according to claim 4, wherein the interruption part interrupts a simulation of a scenario with a probability that depends on an evaluation predicted by the prediction part. 7. The information processing apparatus according to claim 4, wherein, in response to the interruption of the simulation, the interruption part makes the simulation part start a simulation under a different simulation condition. 8. The information processing apparatus according to claim 7, wherein the prediction part calculates a prediction value of the evaluation at an end point of the simulation, and predicts whether the result of the simulation is good or bad based on the calculated prediction value. 9. The information processing apparatus according to claim 8, wherein the generation part generates the characteristic data based on the number of agents in each of the plurality of states at a plurality of points in time in the simulation, and the prediction part calculates the prediction value of the evaluation at the end point of the simulation from the characteristic data based on the number of agents at the plurality of points in time. 10. The information processing apparatus according to claim 9, wherein the generation part generates the characteristic data further based on the evaluation in the middle of the simulation. 11. An information processing method executed by a computer, comprising: a counting stage of counting the number of agents in each of a plurality of states at a middle of a simulation that involves a plurality of agents; and a generation stage of generating characteristic data used for prediction of a result of the simulation based on the number of agents in each of the plurality of states. 12. A machine-readable storage medium encoded with instructions executable by a processor, the machine-readable storage medium comprising: instructions to count the number of agents in each of a plurality of states at a middle of a simulation that involves a plurality of agents; and instructions to generate characteristic data used for prediction of a result of the simulation based on the number of agents in each of the plurality of states. 13. The machine-readable storage medium according to claim 12, further comprising: instructions to predict whether the simulation result is good or bad based on the characteristic data. 14. The machine-readable storage medium according to claim 13, further comprising: instructions to perform the simulation under a plurality of simulation conditions; and instructions to learn from a plurality of pieces of characteristic data generated in the middle of the simulations under the respective simulation conditions and a plurality of corresponding simulation results. 15. The machine-readable storage medium according to claim 14, further comprising: instructions to interrupt the simulation in response to a prediction that the result of the simulation is bad. 16. The machine-readable storage medium according to claim 15, wherein the instructions to interrupt change a level for interruption of a simulation based on a predefined number of top-ranked evaluations of a plurality of evaluations obtained by completing the simulations under the plurality of simulation conditions. 17. The machine-readable storage medium according to claim 15, wherein the instructions to interrupt interrupt a simulation of a scenario with a probability that depends on an evaluation predicted by the instructions to predict. 18. The machine-readable storage medium according to claim 15, wherein, in response to the interruption of the simulation, the instructions to interrupt make the instructions to perform the simulation start a simulation under a different simulation condition. 19. The machine-readable storage medium according to claim 18, wherein the instructions to predict calculate a prediction value of the evaluation at an end point of the simulation, and predicts whether the result of the simulation is good or bad based on the calculated prediction value. 20. The machine-readable storage medium according to claim 19, wherein the instructions to generate generate the characteristic data based on the number of agents in each of the plurality of states at a plurality of points in time in the simulation, and the instructions to predict calculate the prediction value of the evaluation at the end point of the simulation from the characteristic data based on the number of agents at the plurality of points in time.