27. A computer implemented method for dynamic task selection as set forth in claim 26 , wherein the EXIN schema is created by further combining the spatio-temporal schema with the bimodal spatio-temporal schema, the reward input, the punishment input, the emotional state, and the motivational state; wherein the motor schema is created by further combining the spatial schema and the bimodal spatio-temporal schema with the multimodal spatio-temporal schema, the motor system structures, and the EXIN schema; and wherein the sensory inputs are selected from a group consisting of: visual inputs, auditory inputs, kinematic inputs, tactile inputs, olfactory inputs, somatosensory inputs, and motor inputs.
27. A computer implemented method for dynamic task selection as set forth in claim 26 , wherein the EXIN schema is created by further combining the spatio-temporal schema with the bimodal spatio-temporal schema, the reward input, the punishment input, the emotional state, and the motivational state; wherein the motor schema is created by further combining the spatial schema and the bimodal spatio-temporal schema with the multimodal spatio-temporal schema, the motor system structures, and the EXIN schema; and wherein the sensory inputs are selected from a group consisting of: visual inputs, auditory inputs, kinematic inputs, tactile inputs, olfactory inputs, somatosensory inputs, and motor inputs. 28. A computer implemented method for dynamic task selection as set forth in claim 27 , wherein the operations performed by the processor are defined by differential equations with timing constraints that are implemented on a serial computer or on a parallel Analog Pulse Processing computer; wherein the EXIN schema corresponds to compressed representations of an EXternal motivator and INternal states and the motor schema corresponds to a sequence of joint rotations, where space corresponds to the joint rotations and time corresponds to a course taken by the joint rotations along the particular action; and wherein the EXIN schemas, the motor schemas, and the spatio-temporal schemas are encoded and recognized via a spatio-temporal algorithm selected from a group consisting of: hierarchical Adaptive Resonance Theory Store (hARTSTORE) network, hierarchical temporal memory (HTM), sequence of clusters (SOC), and deep belief network (DBN).