<p>This dissertation aim is to investigate the application of higher-ordered feedback architectures, as a control system for an autonomous robot, on delayed response task problems in the area of evolutionary robotics. For the two architectures of interest a theoretical and practical experiment study is conducted to elaborate how these architectures cope with the road-sign problem, and extended versions of the same. In the theoretical study conducted in this dissertation focus is on the features of the architectures, how they behave and act in different kinds of road-sign problem environments in earlier work. Based on this study two problem environments are chosen for practical experiments. The two experiments that are tested are the three-way and multiple stimuli road-sign problems. Both architectures seams to be cope with the three-way road-sign problem. Although, both architectures are shown to have difficulties solving the multiple stimuli road-sign problem with the current experimental setting used.</p><p>This work leads to two insights in the way these architectures cope with and behave in the three-way road-sign problem environment and delayed response tasks. The robot seams to learn to explicitly relate its actions to the different stimuli settings that it is exposed to. Firstly, both architectures forms higher abstracted representations of the inputs from the environment. These representations are used to guide the robots actions in the environment in those situations were the raw input not was enough to do the correct actions. Secondly, it seams to be enough to have two internal representations of stimuli setting and offloading some stimuli settings, relying on the raw input from the environment, to solve the three-way road-sign problem.</p><p>The dissertation works as an overview for new researchers on the area and also as take-off for the direction to which further investigations should be conducted of using higher-ordered feedback architectures.</p>

This dissertation aim is to investigate the application of higher-ordered feedback architectures, as a control system for an autonomous robot, on delayed response task problems in the area of evolutionary robotics. For the two architectures of interest a theoretical and practical experiment study is conducted to elaborate how these architectures cope with the road-sign problem, and extended versions of the same. In the theoretical study conducted in this dissertation focus is on the features of the architectures, how they behave and act in different kinds of road-sign problem environments in earlier work. Based on this study two problem environments are chosen for practical experiments. The two experiments that are tested are the three-way and multiple stimuli road-sign problems. Both architectures seams to be cope with the three-way road-sign problem. Although, both architectures are shown to have difficulties solving the multiple stimuli road-sign problem with the current experimental setting used. This work leads to two insights in the way these architectures cope with and behave in the three-way road-sign problem environment and delayed response tasks. The robot seams to learn to explicitly relate its actions to the different stimuli settings that it is exposed to. Firstly, both architectures forms higher abstracted representations of the inputs from the environment. These representations are used to guide the robots actions in the environment in those situations were the raw input not was enough to do the correct actions. Secondly, it seams to be enough to have two internal representations of stimuli setting and offloading some stimuli settings, relying on the raw input from the environment, to solve the three-way road-sign problem. The dissertation works as an overview for new researchers on the area and also as take-off for the direction to which further investigations should be conducted of using higher-ordered feedback architectures.