This thesis considers the problem of search of an unknown environment by multiple solitary robots: self-interested robots without prior knowledge about each other, and with restricted perception and communication capacity. When solitary robots accidentally interact with each other, they can leverage each other’s information to work more effectively. In this thesis, we consider three problems…
The problem of coordination without a priori information about the environment is important in robotics. Applications vary from formation control to search and rescue.This paper considers the problem of search by a group of solitary robots: self-interested robots without a priori knowledge about each other, and with restricted communication capacity. When the capacity of robots…
This paper is concerned with distributed detection of central nodes in complex networks using closeness centrality. Closeness centrality plays an essential role in network analysis. Evaluating closeness centrality exactly requires complete knowledge of the network; for large networks, this may be inefficient, so closeness centrality should be approximated. Distributed tasks such as leader election can…
We propose a method for combining probabilistic outputs of classifiers to make a single consensus class prediction when no further information about the individual classifiers is available, beyond that they have been trained for the same task. The lack of relevant prior information rules out typical applications of Bayesian or Dempster-Shafer methods, and the default…
This essay reviews human observer-based methods employed in shark spotting in Muizenberg Beach. It investigates Machine Learning methods for automated shark detection with the aim of enhancing human observation. A questionnaire and interview were used to collect information about shark spotting, the motivation of the actual Shark Spotter program and its limitations. We have defined…
Data science Data science (ds) is an interdisciplinary field that uses scientific methods or algorithms to extract knowledge and insights from raw data. Extracted knowledge and actionable insights from data are applied across a broad range of application domains. Data science is related to data mining, machine learning and big data. Artificial Intelligence Artificial intelligence…