arXiv:2209.09979
공식 코드 · Papers with Code
jsdp: a Java Stochastic DP Library
원문 초록
Stochastic Programming is a framework for modelling and solving problems of decision making under uncertainty. Stochastic Dynamic Programming is a branch of Stochastic Programming that takes a "functional equation" approach to the discovery of optimal policies. By leveraging constructs - lambda expressions, functional interfaces, collections and aggregate operators - implemented in Java to operationalise the MapReduce framework, jsdp provides a general purpose library for modelling and solving Stochastic Dynamic Programs.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Toward Explainable Offline RL: Analyzing Representations in Intrinsically Motivated Decision Transformers
The Gittins Index: A Design Principle for Decision-Making Under Uncertainty
Cognitive Guardrails for Open-World Decision Making in Autonomous Drone Swarms
Graph-Structured Data Analysis of Component Failure in Autonomous Cargo Ships Based on Feature Fusion
Guiding LLM Decision-Making with Fairness Reward Models
InvestAlign: Overcoming Data Scarcity in Aligning Large Language Models with Investor Decision-Making Processes under Herd Behavior
토론
이 논문과 연결된 포럼 글이 아직 없습니다.