Optimization over Time
E695664
"Optimization over Time" is a seminal work by Peter Whittle that develops mathematical methods for making optimal sequential decisions in dynamic and stochastic systems.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Optimization over Time canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T7853056 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Optimization over Time Context triple: [Peter Whittle, notableWork, Optimization over Time]
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A.
Convex Optimization
Convex Optimization is a widely used graduate-level textbook that systematically develops the theory, algorithms, and applications of convex optimization problems in engineering, statistics, and applied mathematics.
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B.
Nonlinear programming
Nonlinear programming is a branch of mathematical optimization focused on finding optimal solutions to problems where the objective function or constraints are nonlinear.
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C.
Pontryagin maximum principle
The Pontryagin maximum principle is a fundamental result in optimal control theory that provides necessary conditions for an optimal control process by characterizing optimal trajectories via a Hamiltonian maximization condition.
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D.
Mathematical Theory of Optimal Processes
Mathematical Theory of Optimal Processes is a foundational work in control theory that systematically develops the mathematical principles of optimal control, including what is now known as Pontryagin’s maximum principle.
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E.
Introduction to Stochastic Control Theory
Introduction to Stochastic Control Theory is a foundational textbook that systematically develops the theory and methods for controlling dynamical systems under uncertainty using probabilistic and stochastic-process tools.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Optimization over Time Target entity description: "Optimization over Time" is a seminal work by Peter Whittle that develops mathematical methods for making optimal sequential decisions in dynamic and stochastic systems.
-
A.
Convex Optimization
Convex Optimization is a widely used graduate-level textbook that systematically develops the theory, algorithms, and applications of convex optimization problems in engineering, statistics, and applied mathematics.
-
B.
Nonlinear programming
Nonlinear programming is a branch of mathematical optimization focused on finding optimal solutions to problems where the objective function or constraints are nonlinear.
-
C.
Pontryagin maximum principle
The Pontryagin maximum principle is a fundamental result in optimal control theory that provides necessary conditions for an optimal control process by characterizing optimal trajectories via a Hamiltonian maximization condition.
-
D.
Mathematical Theory of Optimal Processes
Mathematical Theory of Optimal Processes is a foundational work in control theory that systematically develops the mathematical principles of optimal control, including what is now known as Pontryagin’s maximum principle.
-
E.
Introduction to Stochastic Control Theory
Introduction to Stochastic Control Theory is a foundational textbook that systematically develops the theory and methods for controlling dynamical systems under uncertainty using probabilistic and stochastic-process tools.
- F. None of above. chosen
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
academic monograph
ⓘ
book ⓘ |
| author | Peter Whittle NERFINISHED ⓘ |
| contribution |
develops rigorous framework for sequential decision problems
ⓘ
formalizes optimization in dynamic and stochastic environments ⓘ |
| describedAs | seminal work on mathematical methods for optimal sequential decisions ⓘ |
| field |
applied probability
ⓘ
dynamic programming ⓘ operations research ⓘ sequential decision theory ⓘ stochastic control ⓘ |
| hasApplicationDomain |
economics and finance
ⓘ
engineering systems control ⓘ operations management ⓘ queueing systems ⓘ |
| hasMathematicalTool |
Markov decision process formulation
ⓘ
convex analysis ⓘ dynamic programming recursion ⓘ functional equations ⓘ measure-theoretic probability ⓘ stochastic process theory ⓘ |
| influencedField |
applied probability
ⓘ
control theory ⓘ economics ⓘ operations research NERFINISHED ⓘ |
| language | English ⓘ |
| topic |
Bellman equations
NERFINISHED
ⓘ
Lagrange multipliers in dynamic optimization ⓘ Markov chains NERFINISHED ⓘ Markov decision processes NERFINISHED ⓘ average cost criteria ⓘ control of queues ⓘ convexity in dynamic programming ⓘ discounted cost criteria ⓘ dynamic programming equations ⓘ dynamic programming principle ⓘ dynamic systems ⓘ finite-horizon problems ⓘ infinite-horizon problems ⓘ inventory control ⓘ optimal control ⓘ optimal sequential decisions ⓘ resource allocation over time ⓘ semi-Markov processes ⓘ stationary policies ⓘ stochastic optimization ⓘ stochastic systems ⓘ stopping problems ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Optimization over Time Description of subject: "Optimization over Time" is a seminal work by Peter Whittle that develops mathematical methods for making optimal sequential decisions in dynamic and stochastic systems.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.