Agent-Based Control of Decentralised Systems
In this research endeavour, we aim to develop flexible and robust methods for managing decentralised data fusion. We will be developing an agent-based control system for data fusion that:
- operates in a decentralised way while exhibiting desirable system-wide characteristics
- produces effective local decisions that contribute towards an effective overall system (emerging behaviour)
- operates in a computationally efficient manner
We will be using market-based approaches to view management of data fusion activities from an economic point of view and investigate market design for structuring marketplace to achieve various properties such as Pareto optimality, fairness and stability. In order to maximise their individual utility in such markets, strategies will be designed for agents while keeping in mind the overall protocol of the marketplace. These strategies can be augmented through adaptive behaviour (for example though some form of Q-Learning) that aims to utilise knowledge gained from past interactions.
Through this research project, we aim to develop novel market-based control algorithms (together with a simple demonstrator) that evaluate the effectiveness of decentralised control using market-based techniques. This research will also provide a theoretical analysis of the marketplace design to determine its effectiveness, efficiency and predictability and a systematic evaluation of the system's operational performance.
Type: Normal Research Project
Research Groups: Intelligence, Agents, Multimedia Group, Agents, Interaction and Complexity
Themes: Agent Based Computing, E-Business Technologies, Machine Learning, Decentralised Information Systems
Dates: 1st October 2003 to 30th September 2006
- Defence Technology Centre on Data and Information Fusion
- Etty David
- Xudong Luo
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