dynamic programming-based heuristic
MODIFIED ACTION VALUE METHOD APPLIED TO ‘n’-ARMED BANDIT PROBLEMS USING REINFORCEMENT LEARNING
... Reinforcement Learning is learning from interactions with an environment, from the consequences of action, rather than from explicit teaching. It is essentially a simulation-based dynamic programming ...
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Locus-aware decomposition of gene trees with respect to polytomous species trees
... ) dynamic programming algorithm for LTI and a near linear time heuristic for CLTI designed to solve large ...method based on the model of evolu- tionary scenarios with ...
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A dynamic multiarmed bandit gene expression programming hyper heuristic for combinatorial optimization problems
... - If the scanned element is a function (F) with n (n>=1) arguments, then the next n elements are attached below it as its n children. If the scanned element is a terminal (T), then it will form a leaf of the ...
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Extracting Dynamics Matrix of Alignment Process for a Gimbaled Inertial Navigation System Using Heuristic Dynamic Programming Method
... Comparing (36) and (39) shows that the proposed estimation method works properly. In [13], another closed-loop subspace identification method which is based on the least-square problem is presented. In this ...
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NODES PRIORITIZATION TRAVELLING SALESMAN PROBLEM
... used dynamic programming approach in reducing the problem and applied greedy heuristic in an ant colony optimisation algorithm to attain optimal and node prioritised solutions to travelling salesman ...
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The automatic design of hyper heuristic framework with gene expression programming for combinatorial optimization problems
... of heuristic selection mechanisms and acceptance criteria exist, no heuristic selection mechanisms or acceptance criteria so far presented are the best, or the most suitable, across all domains ...which ...
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ComponentJ: A Component-Based Programming Language with Dynamic Reconfiguration
... component-based programming and automated software downloading challenges, such as com- ponent updating at runtime, and silent software modification (minimum human ...the dynamic re- configuration ...
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NEW METHOD FOR SHAPE RECOGNITION BASED ON DYNAMIC PROGRAMMING
... In this paper we present a new method for shape recognition based on dynamic programming. First, each contour of shape is represented by a set of points. After alignment and matching between two ...
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Dynamic Multi-Objective Navigation in Urban Transportation Network Using Ant Colony Optimization
... Route finding problem and navigation are important issues in transportation systems and researchers are still trying to find better solutions in solving them under different circumstances. Different categories are ...
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Optimization of Dynamic Provisioning and Scheduling Based on Budget and Deadline Constraints
... The dynamic framework is an online calculation that arrangements assets and timetables errands at runtime of ...[23]. dynamic provisioning system depends on asset usage under the ...
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Mathematical Model for Dynamic Pump Wavelength Selection Switch
... the heuristic matching algorithm in ...the heuristic matching algo- rithm achieves the same performance as the optimum solution provided by the mathematical ...
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Dynamic Slicing of Aspect-Oriented Programs
... SDG is that the weaving process is not represented cor- rectly. For example, there should be a weaving edge be- tween vertices 15 and 4, beacause, after the execution of before advice at statement 14, the actual ...
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Dynamic Programming Algorithms for Transition Based Dependency Parsers
... Dynamic programming algorithms, also known as tabular or chart-based algorithms, are at the core of many applications in natural language processing. When applied to formalisms such as context-free ...
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A genetic programming hyper heuristic for the multidimensional knapsack problem
... Genetic programming is one of the more recently developed classes of evolutionary algorithms proposed by Koza ...genetic programming as a hyper-heuristic to generate new heuristics and survey ...
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Solving The Printed Circuit Board Drilling Problem By Ant Colony Optimization Algorithm
... Ant Colony Optimization (ACO) algorithm is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. Proposed by Marco Dorigo in 1992, the first algorithm was ...
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Automating the packing heuristic design process with genetic programming
... constructive heuristic to pack the fixed order. Usually a heuristic is used that has performed well in previous ...bottom-left-fill heuristic performs better on average for the 2D strip packing ...
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An Application of Genetic Network Programming Model for Pricing of Basket Default Swaps (BDS)
... independence. Based on this model, some systematic factors influence the default intensities of all assets in the portfolio, so that default times and default intensities of assets are independent of each ...
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Separator-Based Pruned Dynamic Programming for Steiner Tree
... tree can be obtained by recursively applying these two op- erations, and therefore, we can solve the problem by com- puting a minimum Steiner tree for terminals S ∪ {u} for every subset S ⊆ A and every vertex u ∈ V in a ...
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Induction of Non-Monotonic Logic Programs to Explain Boosted Tree Models Using LIME
... Figure 3 shows the “feature importance” plot calculated by xgboost algorithm. Generally, importance provides a score that indicates how useful or valuable each feature was in the construction of the boosted decision ...
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A Quality of Service (QoS) Driven Automatic Service Composition Algorithm
... in dynamic programming and the optimal combination result ...given based on the ...algorithm based on the reachability of graphs as well as the filtering algorithm based on counting and ...
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