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Programim Dinamik×Mësimi i thellë i përforcuar×Programim me numra të plotë×
FushaOptimizimiMësimi i thellëOptimizimi
FamiljaProcess / pipelineMachine learningProcess / pipeline
Viti i origjinës195720151958
KrijuesiRichard BellmanMnih, V. et al. (DQN)Ralph Gomory (cutting planes, 1958); land-and-doig branch-and-bound (1960)
LlojiExact combinatorial optimization via recursive decompositionSequential decision-making (agent–environment interaction)Mathematical optimisation — exact combinatorial method
Burimi themeluesBellman, R. (1957). Dynamic Programming. Princeton University Press. ISBN: 978-0-691-07951-6Mnih, V. et al. (2015). Human-Level Control through Deep Reinforcement Learning. Nature, 518, 529–533. DOI ↗Wolsey, L.A. (1998). Integer Programming. Wiley. ISBN: 9780471283669
Emërtime të tjeraDP, Bellman's Principle of Optimality, Recursive Optimization, Dinamik ProgramlamaDerin Pekiştirmeli Öğrenme (DQN / PPO / A3C), derin pekiştirmeli öğrenme, deep RL, DRLIP, MIP, mixed-integer programming, mixed-integer linear programming
Të lidhura344
PërmbledhjaDynamic Programming (DP) is an exact optimization technique introduced by Richard Bellman in 1957 for solving multi-stage decision problems. It decomposes a complex problem into simpler, overlapping subproblems, solves each subproblem once, and stores the results to avoid redundant computation. Grounded in the Principle of Optimality, DP guarantees globally optimal solutions whenever the problem exhibits overlapping subproblems and optimal substructure.Deep Reinforcement Learning combines neural networks with reinforcement learning so an agent learns by interacting with an environment, popularised by Mnih and colleagues' 2015 Nature work on human-level Atari control. Instead of learning from a fixed labelled dataset, the agent takes actions, observes rewards, and gradually shapes a policy that maximises long-run return.Integer programming (IP), also called mixed-integer programming (MIP) when only some variables are restricted to whole numbers, is a branch of mathematical optimisation in which some or all decision variables must take integer or binary values. Building on linear programming, it was formalised through Ralph Gomory's cutting-plane method (1958) and the Land-and-Doig branch-and-bound algorithm (1960), and it has since become the standard exact framework for scheduling, assignment, routing, and resource-allocation problems.
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ScholarGateKrahasoni metodat: Dynamic Programming · Deep Reinforcement Learning · Integer Programming. Marrë më 2026-06-15 nga https://scholargate.app/sq/compare