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—Cloud computing model separates usage from ownership in terms of control on resource provisioning. Resources in the cloud are projected as a service and are realized using various service models like IaaS, PaaS and SaaS. In IaaS model, end users get to use a VM whose capacity they can specify but not the placement on a specific host or with which other VMs(More)
An efficient, local image-based approach for extraction of intransient facial features and recognition of four facial expressions from 2D image sequences is presented. The algorithm uses edge projection analysis for feature extraction and creates a dynamic spatio-temporal representation of the face, followed by classification through a feed-forward net with(More)
An important approach for efficient inference in probabilistic graphical models exploits symmetries among objects in the domain. Symmetric variables (states) are collapsed into meta-variables (meta-states) and inference algorithms are run over the lifted graphical model instead of the flat one. Our paper extends existing definitions of symmetry by(More)
Many traditional AI algorithms fail to scale as the size of state space increases exponentially with the number of features. One way to reduce computation in such scenarios is to reduce the problem size by grouping symmetric states together and then running the algorithm on the reduced problem. The focus of this work is to exploit symmetry in problems of(More)
ions are a useful tool for computing policies in large domains modeled as a Markov Decision Process. Prior work in this field is mostly focused on developing different notions for state abstractions. In this paper, we develop a novel framework for abstractions, which unifies prior work and directly exploits symmetry at the state-action pair level, thereby(More)
BACKGROUND Mass gatherings including a large number of people makes the planning and management of the event a difficult task. Kumbh Mela is one such, internationally famous religious mass gathering. It creates the substantial challenge of creating a temporary city in which millions of people can stay for a defined period of time. The arrangements need to(More)
Monte-Carlo Tree Search (MCTS) algorithms such as UCT are an attractive online framework for solving planning under uncertainty problems modeled as a Markov Decision Process. However, MCTS search trees are constructed in flat state and action spaces, which can lead to poor policies for large problems. In a separate research thread, domain abstraction(More)