In some artificial systems, performing the realistic perception for actors which will handle both the processes to simulate the sensing organs and identify, will spend most computational time. Unfortunately, this matter even ruins the result of decision based on perception. In order to reduce the computation cost from a systemic view and optimize the performance of system, a brand-new coherent framework was proposed. The framework, which is a cycle of internal-state activizing desire, desire guiding perception, decision making based on perception, and the executing result feed backing to actor, mimics the principle that the behavior of the actor is excitated both by the internal motivation and external stimuli. Firstly, we modeled internal state of artificial actors, which caused by temporary stimuli and accumulation of physical and mental states. Secondly, the actors’ desires were described which are generated by internal state and used for guiding perception. Thirdly, the net value of the possible features combinations for a given desire was figured out using decision-theoretic principles to determine whether the process on the features combinations is worthy or not. Then, a multi-objective decision making algorithm was introduced to achieve decision based on perception, thus the connection between the actual desires and behaviors are established. Finally, we validate the approach and algorithms in establishing an autonomous computer animation system by simulating the realistic behavior of fish in bio-system.