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 20 of 107 for “"partially observable"”.
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Reasoning and decisions in partially observable games
… current limits of parallelism for fully observable games. The third challenge that we address is making decisions in an environment where observation, deliberation, and action are interleaved. Nash equilibrium solutions are a function of the entire game tree and are predicated on the …
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A primer on partially observable Markov processes
Thesis (B.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1982.
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Discrete Approximate Information States in Partially Observable Environments
… state representations for control in partially observable systems. They proposed particular learning objectives which attempt to reconstruct the cost and next state and provide a bound on the suboptimality of the closed-loop performance, but it is unclear whether these bounds are tight …
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Decoding and control procedures for partially observable Markov processes
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1982.
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Distributionally robust optimization for design under partially observable uncertainty
Deciding how to represent and manage uncertainty is a vital part of designing complex systems. Widely used is a probabilistic approach: assigning a probability distribution to each uncertain parameter. However, this presents the designer with the task of assuming these probability distributions or …
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Bayesian nonparametric approaches for reinforcement learning in partially observable domains
… contexts related to reinforcement learning in partially-observable domains: learning partially observable Markov Decision processes, taking advantage of expert demonstrations, and learning complex hidden structures such as dynamic Bayesian networks. In each of these contexts, Bayesian …
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A partially observable approach to allocating resources in a dynamic battle scenario
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.
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Guidance laws for partially-observable UAV interception based on linear covariance analysis
Unmanned Aerial Vehicles (UAVs) have proliferated the skies in recent years as they have become extremely popular for all different kinds of commercial, government, and recreational usage. With all this activity, there remains an open security threat, particularly to airports, soldiers, and large …
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Approximate solution methods for partially observable Markov and semi-Markov decision processes
… methods for discrete-time infinite-horizon partially observable Markov and semi-Markov decision processes (POMDP and POSMDP). One of the main contributions of this thesis is a lower cost approximation method for finite-space POMDPs with the average cost criterion, and its extensions to …
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Dealing with uncertainty : a comparison of robust optimization and partially observable Markov decision processes
… to formulate a problem. Robust optimization and partially observable Markov decision processes (POMDPs) are two methods of dealing with uncertainty in real life problems. Robust optimization is used primarily in operations research, while engineers will be more familiar with POMDPs. For a …
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Partially Observable Markov Process Decision Modeling for the Optimal Maintenance of Oil and Gas Pipelines
Partially Observable Markov Decision Process (POMDP) frameworks are employed across various fields. This dissertation studies the applications of POMDP for maintaining oil and gas pipelines. Pipeline maintenance operations comprise several uncertain elements, especially when addressing …
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Decentralized control of multi-robot systems using partially observable Markov Decision Processes and belief space macro-actions
… spaces with partial observability. Decentralized Partially Observable Markov Decision Processes (Dec-POMDPs) are general models for multi-robot coordination problems. However, representing and solving Dec-POMDPs is often intractable for large problems. This thesis extends the Dec-POMDP framework …
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An integrated performance model learning and planning approach for optimal infrastructure facility maintenance under partial observability
… maintenance decision making is a stochastic and partially observable problem. This thesis presents a learning and decision-making approach for developing optimal joint inspection and maintenance policies for civil infrastructure facilities under performance model uncertainty and partially …
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Manufacturing Technology Adoption in Dynamic Product Environments
… problem: Stochastic Processes in the form of a Partially Observable Markov Decision Process, Non-Linear Mathematical Programming, and Computer Simulation integrated with a Multi-attribute Model based on measurement theory.
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Generalizable Long-Horizon Robotic Manipulation under Uncertainty and Partial Observability
… accomplish complex, long-horizon tasks in novel, partially observable environments. In these scenarios, agents must effectively reason about uncertainty, generalize from limited experiences, and proactively plan actions to acquire missing information. This thesis tackles these core challenges by …
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Learning compositional dynamics models for model-based control
… like Interaction Networks only work for fully observable systems; they also only consider pairwise interactions within a single time step, both restricting their use in practical systems. We introduce Propagation Networks (PropNets), a differentiable, learnable dynamics model that handles …
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Mode identification using stochastic hybrid models with applications to conflict detection and resolution
… probability distributions. In other words an unobservable stochastic process (hidden) that can only be observed through another set of stochastic processes that generate the sequence of observations. The problem of self separation in distributed air traffic management reduces to the ability of …
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Bayesian learning for multi-agent coordination
… challenges are decision making in uncertain and partially-observable environments, and coordination with other agents in such environments. Although uncertainty and coordination have been tackled as separate problems, formal models for an integrated approach are typically restricted to simple …
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Computationally Efficient Reinforcement Learning under Partial Observability
… to fully observe the latent state of the system. Partially observable Markov decision processes (POMDPs) are a generalization of Markov decision processes (MDPs) that model this challenge. Unfortunately, planning and learning near-optimal policies in POMDPs is computationally intractable. Most …
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A Language and Logic for Programming and Reasoning with Partial Observability
Computer systems are increasingly deployed in partially-observable environments, in which the system cannot directly determine the environment’s state but receives partial information from observations. When such a computer system executes, it risks forming an incorrect belief about the true state …
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