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In this study, we investigate the utilization of a multi-objective approach in evolving artificial neural networks (ANNs) for an autonomous mobile robot. The ANN acts as a controller for radio frequency (RF)-localization behavior of a Khepera robot simulated in a 3D physics-based environment. The elitist Pareto-frontier Differential Evolution (PDE) algorithm is used to generate the Pareto optimal...
Transparency perception is recognized as one of the important phenomena for the theory of early vision. This is because transparency perception suggests that a simple theory reconstructing a single-valued field of a visual attribute, such as an optical-flow field, cannot model the neural mechanism in the brain and raises the fundamental issue of how the visual attribute is represented and computed...
The Federal Reserve determines federal funds target rate (FFTR), which is one of the most publicized and anticipated economic indicator in the financial world. As the decision making process is complex due to unknown functions, it has been a difficult and challenging process for the researcher to model the thoughts of the Federal Open Market Committee (FOMC) members using statistical methods and hence...
This paper discusses the structured learning based on associative memory of partner robots through interaction with people. Human interaction based on gestures is very important to realize the natural communication. The meaning of gestures can be understood through intentional interactions with a human. Therefore, we propose a method for associative learning based on intentional interaction and conversation...
Releasing a software at the right time is crucial to any software house. A set of critical questions that any software project manager has to deal with: ldquoIs the software under development ready to be released now?rdquo, ldquoHow many faults are remaining in the software?rdquo, ldquoHow many changes are required to correct the errors?rdquo, ldquoHow much time is needed to change the programs?rdquo...
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