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Intelligence, 2(3):251-270. Dickmanns, E. D. 2000. An expectation-based, multi-focal, saccadic (EMS) vision system for vehicle guidance. Paper presented at the International Symposium of Robotics Research (ISRR’99), 421-430, Snowbird Utah, USA. Dong, D., and Franklin, S. 2014. Sensory Motor System: Modeling the process of action execution. Paper presented at the Proceedings of the 36th Annual Conference of the Cognitive Science Society, 2145-2150, Austin TX, USA. Duch, W., Oentaryo, R. J., and Pasquier, M. 2008. Cognitive Architectures: Where do we go from here? Paper

-perception cycle for postural control in a moving visual environment. Experimental Brain Research, 97 (3), 477-486. Dong, D., & Franklin, S. (2014). Sensory Motor System: Modeling the process of action execution. Paper presented at the Proceedings of the 36th Annual Conference of the Cognitive Science Society. Dong, D., & Franklin, S. (2015). A New Action Execution Module for the Learning Intelligent Distribution Agent (LIDA): The Sensory Motor System. Cognitive Computation . doi: 10.1007/s12559-015-9322-3. Dorner, D., & Hille, K. (1995). Artificial souls: motivated

caused by the manipulation of the level of opposition may be different according to the technical-tactical action studied. There are also studies that have found differences between the actions of passing and dribbling after the application of different teaching models. These emphasize the effectiveness of the technical teaching model for dribbling and the tactical model for passing ( Psotta and Martin, 2011 ). A recent study aimed to analyze differences in decision making and action execution after a program of intervention based on the Teaching Games for

, decision making, affordance extraction, action planning and action execution (step 1). Once these powers are successfully mastered, then these systems may be embodied into a robot able to act in the real world (step 2). Their embodiment, however, cannot guarantee that these systems will be able to operate autonomously in the environment as they will still need to solve the issues of the real-time system operation, resource management and meta-learning (step 2). In their article “Cognitive architectures and autonomy: a comparative review” Thórisson and