Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 7 of 7 for “"multi-agent communication"”.
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Multi-agent Communication Protocols with Emergent Behaviour
The emergent behaviour of a multiagent system depends on the component agents and how they interact. A critical part of interaction between agents is communication. This thesis presents a multi-agent system communication model for physical moving agents. The work presented in this thesis provides …
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Evolutionary Learning of Goal-Driven Multi-agent Communication
Multi-agent systems are a common paradigm for building distributed systems in different domains such as networking, health care, swarm sensing, robotics, and transportation. Systems are usually designed or adjusted in order to reflect the performance trade-offs made according to the characteristics …
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Learning to Ground Multi-Agent Communication with Autoencoders
Communication requires having a common language, a lingua franca, between agents. This language could emerge via a consensus process between agents, but this may require many generations of trial and error. Alternatively, the lingua franca can be given by the environment, where agents ground their …
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Intelligent Knowledge Distribution for Multi-Agent Communication, Planning, and Learning
… dissertation addresses a fundamental question of multi-agent coordination: what infor- mation should be sent to whom and when, with the limited resources available to each agent? Communication requirements for multi-agent systems can be rather high when an accurate picture of the environment and …
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Interactive media and social exchange of market information
A persistent belief in marketing communication is that consumer word-of-mouth (WOM) plays a crucial role in the diffusion of information in a society. The Internet, the largest network ever created by humans, demonstrates the validity of this wisdom by enabling individual consumers from all over …
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Out-of-distribution generalisation in machine learning
… goal from the perspective of learning from multiple training distributions. The contribution to this line of research is twofold. First, I present a new standardised suite of tasks for evaluation and comparison of out-of-distribution generalisation algorithms. Second, I state a set of new …
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Graph Neural Networks for Multi-Agent Learning
… They are particularly useful in the context of multi-agent learning, where most data is structured as a graph (e.g., communication links in a multi-robot team generate a graph connectivity). In this thesis, we study the field of multi-agent learning. Recent advances in the domain are promising, …