11. A system for dynamic task selection as set forth in claim 1 , wherein the system further comprises an agent to be trained to perform dynamic task selection, an instructor for providing a task to the agent to perform, and a data base of motor schemas that fulfill a plurality of tasks to be selected by the instructor, and wherein the processor further performs the operations of: receiving from the instructor a desired task to be performed by the agent; selecting from the data base a desired motor schema that fulfills the desired task received from the instructor; executing the motor schema created by the system; comparing a difference measurement between the executed motor schema and the desired motor schema; computing a progress measurement of the agent from the reward input and the schema difference measurement, wherein the progress measurement increases as the executed motor schema gets closer to the desired motor schema and closer to achieving the desired task, and wherein the progress measurement decreases as the executed motor schema gets farther away from the desired motor schema; generating a reward signal when the progress measurement increases, indicating that the agent is closer to achieve the desired task; keeping a count of number of reward signals generated by the system to compute reward frequency associated with the created motor schema; generating a punishment signal when the progress measurement decreases, indicating that the agent is not achieving the desired task; keeping a count of number of punishment signals generated by the system; and feeding back the reward signal and punishment signal to be inputted into the system as reward input and punishment input, respectively.
11. A system for dynamic task selection as set forth in claim 1 , wherein the system further comprises an agent to be trained to perform dynamic task selection, an instructor for providing a task to the agent to perform, and a data base of motor schemas that fulfill a plurality of tasks to be selected by the instructor, and wherein the processor further performs the operations of: receiving from the instructor a desired task to be performed by the agent; selecting from the data base a desired motor schema that fulfills the desired task received from the instructor; executing the motor schema created by the system; comparing a difference measurement between the executed motor schema and the desired motor schema; computing a progress measurement of the agent from the reward input and the schema difference measurement, wherein the progress measurement increases as the executed motor schema gets closer to the desired motor schema and closer to achieving the desired task, and wherein the progress measurement decreases as the executed motor schema gets farther away from the desired motor schema; generating a reward signal when the progress measurement increases, indicating that the agent is closer to achieve the desired task; keeping a count of number of reward signals generated by the system to compute reward frequency associated with the created motor schema; generating a punishment signal when the progress measurement decreases, indicating that the agent is not achieving the desired task; keeping a count of number of punishment signals generated by the system; and feeding back the reward signal and punishment signal to be inputted into the system as reward input and punishment input, respectively. 13. A system for dynamic task selection as set forth in claim 11 , wherein the processor further performs the operations of: combining the sensory inputs with the count of reward signals to create a reset toggle signal when the count of reward signals is drastically reduced or the sensory inputs reflect significantly changed emotional states; and sending the reset toggle signal to the multimodal pre-processor, wherein reset toggle signal forces the multimodal pre-processor to stop creating the EXIN schema; and sending the reset toggle signal to the motor system to shut-off motor channels and stop the motor system from performing actions.