Browsing by Author "Gadre, Aditya Shrikant"

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    Learning Strategies in Multi-Agent Systems - Applications to the Herding Problem
    Gadre, Aditya Shrikant (Virginia Tech, 2001-11-30)
    "Multi-Agent systems" is a topic for a lot of research, especially research involving strategy, evolution and cooperation among various agents. Various learning algorithm schemes have been proposed such as reinforcement learning and evolutionary computing. In this thesis two solutions to a multi-agent herding problem are presented. One solution is based on Q-learning algorithm, while the other is based on modeling of artificial immune system. Q-learning solution for the herding problem is developed, using region-based local learning for each individual agent. Individual and batch processing reinforcement algorithms are implemented for non-cooperative agents. Agents in this formulation do not share any information or knowledge. Issues such as computational requirements, and convergence are discussed. An idiotopic artificial immune network is proposed that includes individual B-cell model for agents and T-cell model for controlling the interaction among these agents. Two network models are proposed--one for evolving group behavior/strategy arbitration and the other for individual action selection. A comparative study of the Q-learning solution and the immune network solution is done on important aspects such as computation requirements, predictability, and convergence.
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    Observability Analysis in Navigation Systems with an Underwater Vehicle Application
    Gadre, Aditya Shrikant (Virginia Tech, 2007-01-26)
    Precise navigation of autonomous underwater vehicles (AUV) is one of the most important challenges in the realization of distributed and cooperative algorithms for marine applications. We investigate an underwater navigation technology that enables an AUV to compute its trajectory in the presence of unknown currents in real time and simultaneously estimate the currents, using range or distance measurements from a single known location. This approach is potentially useful for small AUVs which have severe volume and power constraints. The main contribution of this work is observability analysis of the proposed navigation system using novel approaches towards uniform observability of linear time-varying (LTV) systems. We utilize the notion of limiting systems in order to address uniform observability of LTV systems. Uniform observability of an LTV system can be studied by assessing finite time observability of its limiting systems. A new definition of uniform observability over a finite interval is introduced in order to address existence of an observer whose estimation error is bounded by an exponentially decaying function on the finite interval. We also show that for a class of LTV systems, uniform observability of a lower dimensional subsystem derived from an LTV system is sufficient for uniform observability of the LTV system.