Evolutionary robotics controllers with location perception facilitated by neural network-based simulators
- Authors: Phillips, Antin Paul
- Date: 2021-04
- Subjects: Grahamstown (South Africa) , Eastern Cape (South Africa) , Neural networks (Computer science) -- South Africa
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10948/52137 , vital:43444
- Description: Humans impressively maintain a real-time approximation of their bodily form. For instance, one knows where one’s arm is, relative to the body, without needing to directly observe it. This ability, in part, allows humans to interact with the environment without direct observation. This bodily sense is referred to as ”proprioception“. The human body contains various proprioceptors, sensory neurons which provide information about the physical state of the body. This information, along with internal body representations that humans develop over time, allows one to maintain an approximation of their bodily form. Humans also possess an impressive sense of direction and navigation ability. For instance, a blindfolded human can move around a familiar environment and maintain an approximate sense of where they are within that environment. This ability is, in part, enabled by proprioception as it provides one with an approximation of the effects their actions have on their body. The field of Evolutionary Robots (ER) makes extensive use of robotic simulators to carry out simulated robotic evaluations. Research has been conducted into alternate forms of simulation and Simulator Neural Networks (SNNs) were subsequently developed. The speed and accuracy of these SNNs, relative to more typical simulation techniques, is what inspired the approach explored in this research. Robots do not necessarily possess the appropriate hardware to sense their position within an environment. Thus, it was proposed that SNNs could be incorporated into ER controllers to approximate the position of the robot. These SNNs would be executed in parallel to the robot and provide a constant approximation of the robot’s position. This would provide controllers with information that they would not otherwise have, albeit approximate information. Various experiments were carried out which examined both typical ER controllers as well as those which were augmented in the proposed fashion. The augmented controllers were found to outperform typical controllers as well as develop more advanced and efficient behaviours. Furthermore, the augmented controllers demonstrated the ability to solve tasks that regular controllers could not. A potential criticism of the approach suggested in this research is that ER controllers could hypothetically be trained in such a way that the proposed augmentation would be unnecessary. This possibility was investigated and it was found that successfully training controllers in such a manner would be unlikely. Furthermore, the effort involved in fine-tuning this training process would be greater than simply following the approach suggested in this research. Another potential drawback of the suggested approach involved the accuracy of the information that SNNs could provide to controllers. The approximated information was found to diverge over time and negatively affected controller performance. A method to address this issue was proposed and subsequently implemented. This method was demonstrated to be an effective means of reducing the divergence of the SNNs outputs and, in turn, improved controller performance. , Thesis (MSc) -- Faculty of Science, School of Computer Science, Mathematics, Physics and Statistics, 2021
- Full Text: false
- Date Issued: 2021-04
Financing of local economic development initiatives in South Africa
- Authors: Moses, Itumeleng James
- Date: 2021-04
- Subjects: Grahamstown (South Africa) , Eastern Cape (South Africa) , South Africa
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10948/53035 , vital:44864
- Description: Post the 2008/09 global economic and financial crises, increased calls have been made for exploration and consideration of alternative sources of funding for economic development at a local level. To limit dependence on restricted and sometimes dwindling public finances from central government, many countries in the world have considered various alternative forms of financing. In South Africa, only four of the eight metropolitan municipalities (in short metros), have introduced municipal bonds primarily to finance their infrastructure development initiatives. Having noted the reluctance of metros and secondary cities in South Africa to explore alternative sources to finance their local economic development (LED) initiatives, this study advocates for the use of municipal bonds in the Mangaung Metropolitan Municipality (henceforth Mangaung Metro), as an alternative source of finance for its LED initiatives, especially its infrastructure development programme. The study further presents evidence for the other metros in South Africa, where municipal bonds have worked as an additional and/or alternative source of finance. Using analysis of socio-economic conditions as well as selected financial ratios, the study compares Mangaung Metro to the other four metros that have issued municipal bonds in order to assess the state of readiness and the viability of a municipality bond for the metro. On the analysis of socio-economic conditions, this study found that on the one hand, the Mangaung Metro lags all the other metros under review on almost all the indicators, whilst the economic and labour market data highlights the development potential of the metro. On the financial analysis, the study found that Mangaung Metro’s financial situation seems to have been improving and could have been described as sound up to 2015/16, and that the deterioration in the metro’s finance coincided with the changes in the political and 6 administrative leadership and management of the metro. , Thesis (MPhil) -- Faculty of Business and Economic Sciences, School of Economics Development and Tourism, 2021
- Full Text: false
- Date Issued: 2021-04