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Showing 1 to 20 of 220 for “"Decision Processes"”.

  1. Time-dependence in Markovian decision processes.

    The main focus of this thesis is Markovian decision processes with an emphasis on incorporating time-dependence into the system dynamics. When considering such decision processes, we provide value equations that apply to a large range of classes of Markovian decision processes, including Markov …

    adelaide Repository record for Time-dependence in Markovian decision processes. (opens in a new tab)

  2. Perturbation theory and Markovian decision processes.

    Massachusetts Institute of Technology. Dept. of Physics. Thesis. 1965. Sc.D.

    mit Repository record for Perturbation theory and Markovian decision processes. (opens in a new tab)

  3. Hazard avoidance alerting with Markov decision processes

    (cont.) (incident rate and unnecessary alert rate), the MDP-based logic can meet or exceed that of alternate logics.

    mit Repository record for Hazard avoidance alerting with Markov decision processes (opens in a new tab)

  4. Simulation-based optimization of Markov decision processes

    Markov decision processes have been a popular paradigm for sequential decision making under uncertainty. Dynamic programming provides a framework for studying such problems, as well as for devising algorithms to compute an optimal control policy. Dynamic programming methods rely on a suitably …

    mit Repository record for Simulation-based optimization of Markov decision processes (opens in a new tab)

  5. Acceleration of Iterative Methods for Markov Decision Processes

    This research focuses on Markov Decision Processes (MDP). MDP is one of the most important and challenging areas of Operations Research. Every day people make many decisions: today's decisions impact tomorrow's and tomorrow's will impact the ones made the day after. Problems in Engineering, …

    toronto-retro Repository record for Acceleration of Iterative Methods for Markov Decision Processes (opens in a new tab)

  6. An investigation of consumers’ decision processes and styles

    A vast number of new products are launched on to the market every year, 80-90% of which are destined to fail. The aim of the current study was to identify the group of people i.e. market initiators who would be the first to buy a new product. The new product in the current study was polyunsaturated …

    birmingham Repository record for An investigation of consumers’ decision processes and styles (opens in a new tab)

  7. Tensor decomposition and parallelization of Markov Decision Processes

    Markov Decision Processes (MDPs) with large state spaces arise frequently when applied to real world problems. Optimal solutions to such problems exist, but may not be computationally tractable, as the required processing scales exponentially with the number of states. Unsurprisingly, investigating …

    mit Repository record for Tensor decomposition and parallelization of Markov Decision Processes (opens in a new tab)

  8. Developing decision processes for managing supply chain dynamics

    Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1997, and Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.

    mit Repository record for Developing decision processes for managing supply chain dynamics (opens in a new tab)

  9. Learning bounded optimal behavior using Markov decision processes

    … optimization problem is posed within a Markov Decision Process framework and is solved off-line to determine a policy for carrying out computations. Once the optimal policy is determined, it serves efficiently as an online metalevel controller that selects computational actions conditioned upon …

    mit Repository record for Learning bounded optimal behavior using Markov decision processes (opens in a new tab)

  10. Asset Management Data Collection for Supporting Decision Processes

    … collection activities in order to support their decision processes at various levels. However, not all the data collected supply transportation officials with useful information for efficient and effective decision-making. This thesis presents research aimed at formally identifying links between …

    vt Repository record for Asset Management Data Collection for Supporting Decision Processes (opens in a new tab)

  11. Learning and value function approximation in complex decision processes

    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.

    mit Repository record for Learning and value function approximation in complex decision processes (opens in a new tab)

  12. Cognitive Radar Applied To Target Tracking Using Markov Decision Processes

    … coexistence problem is modeled as a Markov decision process (MDP), and reinforcement learning is applied to drive the radar to optimal behavior.

    vt Repository record for Cognitive Radar Applied To Target Tracking Using Markov Decision Processes (opens in a new tab)

  13. Model-free reinforcement learning in non-stationary Markov Decision Processes

    … unknown environment, usually modeled by a Markov Decision Process (MDP). The classical RL literature typically assumes that the state transition functions and the reward functions of the MDP are time-invariant. Such a stationary model, however, cannot capture the dynamic nature of many sequential …

    uiuc Repository record for Model-free reinforcement learning in non-stationary Markov Decision Processes (opens in a new tab)

  14. Decomposition of Time Scales in Linear Systems and Markovian Decision Processes

    The presence of "slow" and "fast" dynamics in large scale systems has motivated the use of singular perturbations as a means of obtaining reduced order models for analysis and control law design. In this thesis we establish how systems having this "two-time-scale" property can use singular …

    uiuc Repository record for Decomposition of Time Scales in Linear Systems and Markovian Decision Processes (opens in a new tab)

  15. Robust, risk-sensitive, and data-driven control of Markov Decision Processes

    Markov Decision Processes (MDPs) model problems of sequential decision-making under uncertainty. They have been studied and applied extensively. Nonetheless, there are two major barriers that still hinder the applicability of MDPs to many more practical decision making problems: * The decision

    mit Repository record for Robust, risk-sensitive, and data-driven control of Markov Decision Processes (opens in a new tab)

  16. The problem of identity in organizational behavior and human decision processes

    Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 1998.

    mit Repository record for The problem of identity in organizational behavior and human decision processes (opens in a new tab)

  17. Adoption of telecommuting : modeling the employer's and the employee's decision processes

    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 1995.

    mit Repository record for Adoption of telecommuting : modeling the employer's and the employee's decision processes (opens in a new tab)

  18. Consequentiality, justification and auditors' decision processes: A theoretical framework and two experiments

    … is known regarding their effects on auditors' decision processes (e.g., Ashton 1990; Gibbins and Newton 1993; Solomon and Shields, in press). In this dissertation, I develop a framework for predicting when justification demands are likely to be of significant influence. Additionally, I …

    uiuc Repository record for Consequentiality, justification and auditors' decision processes: A theoretical framework and two experiments (opens in a new tab)

  19. Policy-based average-reward and robust Markov decision processes and reinforcement learning

    Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo terms

    uiuc Repository record for Policy-based average-reward and robust Markov decision processes and reinforcement learning (opens in a new tab)

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