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Showing 1 to 12 of 12 for “"backward induction"”.

  1. On Backward Induction Paradox

    In this master's thesis some solutions to the backward induction paradox as well as some ways to regain the paradox are examined. Backward induction is a method to solve finite, extensive games of perfect information.The main idea is, roughly, that the players choose the best outcome at each …

    helsinki Repository record for On Backward Induction Paradox (opens in a new tab)

  2. Long Term Policy Goals Under Electoral Competition Given Varied Temporal Discount Rates Among Voters

    … followed by an election, solving the game via backward induction to find the subgame perfect Nash equilibria.

    mit Repository record for Long Term Policy Goals Under Electoral Competition Given Varied Temporal Discount Rates Among Voters (opens in a new tab)

  3. A radial basis function approach to pricing and hedging options incorporating transaction costs

    … without transaction costs using some predefined backward induction performance measures.In addition, we further implemented our RBF network models on the new self-financing hedging strategy developed by Lai & Lim (2004), which is based on minimizing the expected cumulative hedging error and …

    nus Repository record for A radial basis function approach to pricing and hedging options incorporating transaction costs (opens in a new tab)

  4. Sequential Decision Making For Choice Functions On Gambles

    … the solution to that sub-problem. The second, backward induction, requires that the solution of the problem can be found by working backwards from the final stage of the problem, removing everything judged non-optimal at any stage. The third, locality, applies only to special problems such as …

    durham Repository record for Sequential Decision Making For Choice Functions On Gambles (opens in a new tab)

  5. Modeling Multi-level Incentives in Health Care: A Multiscale Decision Theory Approach

    … perfect Nash equilibrium (SPNE) concept and the backward induction principle, and determine the conditions under which the MSSP incentive leads to the desired outcomes of cost reduction and quality of care improvements. In the third part of this thesis, we study the multi-level decision making in …

    vt Repository record for Modeling Multi-level Incentives in Health Care: A Multiscale Decision Theory Approach (opens in a new tab)

  6. Design of Joint Verification-Correction Strategies for Engineered Systems

    … with all conditions of a VP. A modified backward induction method is proposed to solve for an optimal JVCS in small strategy spaces. Third, a UCB-based tree search approach is designed to find near-optimal JVCSs in large strategy spaces. A case study is conducted and analyzed in each step …

    vt Repository record for Design of Joint Verification-Correction Strategies for Engineered Systems (opens in a new tab)

  7. Numerical approaches for sequential Bayesian optimal experimental design

    … approximate dynamic programming method couples backward induction and regression to construct value function approximations. It also iteratively generates trajectories via exploration and exploitation to further improve approximation accuracy in frequently visited regions of the state space. …

    mit Repository record for Numerical approaches for sequential Bayesian optimal experimental design (opens in a new tab)

  8. Game-theoretic methods for security and resilience in cyber-physical systems

    … their equilibrium solutions are characterized by backward induction solving a sequence of nested games. This approach leads to a distributed secure routing protocol that enables the resilience of network routing and self-recovery mechanisms in face of adversarial attacks. Finally, in order to …

    uiuc Repository record for Game-theoretic methods for security and resilience in cyber-physical systems (opens in a new tab)

  9. Incentive mechanism design in blockchain-based federated learning over edge clouds

    … which is solved using a hybrid ADMM and backward induction algorithm. Both approaches demonstrate that optimizing under complete information significantly improves system utility and model accuracy compared to baseline strategies. Finally, the dissertation tackles the realistic constraint …

    temple Repository record for Incentive mechanism design in blockchain-based federated learning over edge clouds (opens in a new tab)

  10. Generalized sequential assignment problem

    … rates). The optimal assignment policy uses backward induction to first solve smaller subproblems, and then use them to optimally assign tasks to workers from the first stage. An approximation algorithm is proposed that achieves a fraction of the optimal reward in a polynomial time. Assuming …

    uiuc Repository record for Generalized sequential assignment problem (opens in a new tab)

  11. Efficient Media Access Control and Distributed Channel-aware Scheduling for Wireless Ad-Hoc Networks

    … analysis. We then analyze the problem using backward induction when the finite horizon constraint cannot be ignored. We develop one recursive approach to solve the problem and show that the computational complexity is linear with respect to network size. We present an improved protocol to …

    maryland Repository record for Efficient Media Access Control and Distributed Channel-aware Scheduling for Wireless Ad-Hoc Networks (opens in a new tab)

  12. Dynamic sequential decision problems with asymmetric information: some existence results

    … of CIMPE is that it can be computed using a backward induction algorithm. Further, if the cost functions of the decision makers are quadratic in their arguments (called LQG games) and satisfy certain conditions, then the game is proven to admit a unique CIMPE, which can be computed by solving …

    uiuc Repository record for Dynamic sequential decision problems with asymmetric information: some existence results (opens in a new tab)