- Browse by Author
Browsing by Author "Gorman, William J."
Now showing 1 - 3 of 3
Results Per Page
Sort Options
Item Decentralized and Partially Decentralized Multi-Agent Reinforcement Learning(2013-08-22) Tilak, Omkar Jayant; Mukhopadhyay, Snehasis; Si, Luo; Neville, Jennifer; Raje, Rajeev; Tuceryan, Mihran; Gorman, William J.Multi-agent systems consist of multiple agents that interact and coordinate with each other to work towards to certain goal. Multi-agent systems naturally arise in a variety of domains such as robotics, telecommunications, and economics. The dynamic and complex nature of these systems entails the agents to learn the optimal solutions on their own instead of following a pre-programmed strategy. Reinforcement learning provides a framework in which agents learn optimal behavior based on the response obtained from the environment. In this thesis, we propose various novel de- centralized, learning automaton based algorithms which can be employed by a group of interacting learning automata. We propose a completely decentralized version of the estimator algorithm. As compared to the completely centralized versions proposed before, this completely decentralized version proves to be a great improvement in terms of space complexity and convergence speed. The decentralized learning algorithm was applied; for the first time; to the domains of distributed object tracking and distributed watershed management. The results obtained by these experiments show the usefulness of the decentralized estimator algorithms to solve complex optimization problems. Taking inspiration from the completely decentralized learning algorithm, we propose the novel concept of partial decentralization. The partial decentralization bridges the gap between the completely decentralized and completely centralized algorithms and thus forms a comprehensive and continuous spectrum of multi-agent algorithms for the learning automata. To demonstrate the applicability of the partial decentralization, we employ a partially decentralized team of learning automata to control multi-agent Markov chains. More flexibility, expressiveness and flavor can be added to the partially decentralized framework by allowing different decentralized modules to engage in different types of games. We propose the novel framework of heterogeneous games of learning automata which allows the learning automata to engage in disparate games under the same formalism. We propose an algorithm to control the dynamic zero-sum games using heterogeneous games of learning automata.Item Design and evaluation of a secure, privacy-preserving and cancelable biometric authentication : Bio-Capsule(2014-09-04) Sui, Yan; Zou, Xukai, 1963-; Bertino, Elisa; Li, Ninghui; Du, Yingzi, 1975-; Li, Feng; Prabhakar, Sunil; Gorman, William J.A large portion of system breaches are caused by authentication failure either during the system login process or even in the post-authentication session, which is further related to the limitations associated with existing authentication approaches. Current authentication methods, whether proxy based or biometrics based, are hardly user-centric; and they either put burdens on users or endanger users' (biometric) security and privacy. In this research, we propose a biometrics based user-centric authentication approach. The main idea is to introduce a reference subject (RS) (for each system), securely fuse the user's biometrics with the RS, generate a BioCapsule (BC) (from the fused biometrics), and employ BCs for authentication. Such an approach is user-friendly, identity-bearing yet privacy-preserving, resilient, and revocable once a BC is compromised. It also supports "one-click sign on" across multiple systems by fusing the user's biometrics with a distinct RS on each system. Moreover, active and non-intrusive authentication can be automatically performed during the user's post-authentication on-line session. In this research, we also formally prove that the proposed secure fusion based BC approach is secure against various attacks and compare the new approach with existing biometrics based approaches. Extensive experiments show that the performance (i.e., authentication accuracy) of the new BC approach is comparable to existing typical biometric authentication approaches, and the new BC approach also possesses other desirable features such as diversity and revocability.Item Video anatomy : spatial-temporal video profile(2014-07-31) Cai, Hongyuan; Zheng, Jiang Yu; Tuceryan, Mihran; Popescu, Voicu Sebastian; Tricoche, Xavier; Prabhakar, Sunil; Gorman, William J.A massive amount of videos are uploaded on video websites, smooth video browsing, editing, retrieval, and summarization are demanded. Most of the videos employ several types of camera operations for expanding field of view, emphasizing events, and expressing cinematic effect. To digest heterogeneous videos in video websites and databases, video clips are profiled to 2D image scroll containing both spatial and temporal information for video preview. The video profile is visually continuous, compact, scalable, and indexing to each frame. This work analyzes the camera kinematics including zoom, translation, and rotation, and categorize camera actions as their combinations. An automatic video summarization framework is proposed and developed. After conventional video clip segmentation and video segmentation for smooth camera operations, the global flow field under all camera actions has been investigated for profiling various types of video. A new algorithm has been designed to extract the major flow direction and convergence factor using condensed images. Then this work proposes a uniform scheme to segment video clips and sections, sample video volume across the major flow, compute flow convergence factor, in order to obtain an intrinsic scene space less influenced by the camera ego-motion. The motion blur technique has also been used to render dynamic targets in the profile. The resulting profile of video can be displayed in a video track to guide the access to video frames, help video editing, and facilitate the applications such as surveillance, visual archiving of environment, video retrieval, and online video preview.