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Search results for: distributed searching
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Distributed graph searching with a sense of direction
PublicationIn this work we consider the edge searching problem for vertex-weighted graphs with arbitrarily fast and invisible fugitive. The weight function w provides for each vertex v the minimum number of searchers required to guard v, i.e., the fugitive may not pass through v without being detected only if at least w(v) searchers are present at v. This problem is a generalization of the classical edge searching problem, in which one has...
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Multi-agent graph searching and exploration algorithms
PublicationA team of mobile entities, which we refer to as agents or searchers interchangeably, starting from homebases needs to complete a given task in a graph.The goal is to build a strategy, which allows agents to accomplish their task. We analyze strategies for their effectiveness (e.g., the number of used agents, the total number of performed moves by the agents or the completion time).Currently, the fields of on-line (i.e., agents...
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Decontaminating Arbitrary Graphs by Mobile Agents: a Survey
PublicationA team of mobile agents starting from homebases need to visit and clean all nodes of the network. The goal is to find a strategy, which would be optimal in the sense of the number of needed entities, the number of moves performed by them or the completion time of the strategy. Currently, the field of distributed graph searching by a team of mobile agents is rapidly expanding and many new approaches and models are being presented...
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Semantic modeling of contextual augmented reality environments
PublicationDespite significant progress in the field of augmented reality (AR), regarding both hardware and software, there is still a lack of universal models and methods that would enable building ubiquitous AR systems that could be used anywhere and anytime, covering different application areas. This dissertation describes a new approach to building AR systems, called the Contextual Augmented Reality Environment (CARE). The CARE approach...