H-DPOP: Using Hard Constraints for Search Space Pruning in DCOP

H-DPOP: Using Hard Constraints for Search Space Pruning in DCOP

In distributed constraint optimization problems, dynamic programming methods have been recently proposed (e.g. DPOP). In dynamic programming many valuations are grouped together in fewer messages, which produce much less networking overhead than search. Nevertheless, these messages are exponential i...

Saved in:

書目詳細資料
Main Authors:	KUMAR, Akshat, PETCU, Adrian, FALTINGS, Boi
格式:	text
語言:	English
出版:	Institutional Knowledge at Singapore Management University 2008
主題:	Artificial Intelligence and Robotics Computer Sciences
在線閱讀:	https://ink.library.smu.edu.sg/sis_research/2215 https://ink.library.smu.edu.sg/context/sis_research/article/3215/viewcontent/H_DPOP__Using_Hard_Constraints_for_Search_Space_Pruning_in_DCOP.pdf
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!
機構:	Singapore Management University
語言:	English

相似書籍

Distributed Constraint Optimization with Structured Resource Constraints
由: KUMAR, Akshat, et al.
出版: (2009)

Incremental DCOP Search Algorithms for Solving Dynamic DCOP Problems
由: YEOH, William, et al.
出版: (2011)

Caching Schemes for DCOP Search Algorithms
由: YEOH, William, et al.
出版: (2009)

Probabilistic Inference Based Message-Passing for Resource Constrained DCOPs
由: GHOSH, Supriyo, et al.
出版: (2015)

Decentralized multi-agent reinforcement learning in average-reward dynamic DCOPs
由: Nguyen, Duc Thien, et al.
出版: (2014)

Decentralized multi-agent reinforcement learning in average-reward dynamic DCOPs
由: NGUYEN, Duc Thien, et al.
出版: (2014)

Using constraint programming and graph representation learning for generating interpretable cloud security policies
由: KAZDAGLI, Mikhail, et al.
出版: (2022)

Taking DCOP to the Real World: Efficient Complete Solutions for Distributed Event Scheduling
由: MAHESWARAN, Rajiv, et al.
出版: (2004)

Distributed Gibbs: A memory-bounded sampling-based DCOP algorithm
由: NGUYEN, Duc Thien, et al.
出版: (2013)

Learning to handle complex constraints for vehicle routing problems
由: BI, Jieyi, et al.
出版: (2024)

Constraint-Based Dynamic Programming for Decentralized POMDPs with Structured Interactions
由: KUMAR, Akshat, et al.
出版: (2009)

Stochastic dominance in stochastic DCOPs for risk-sensitive applications
由: NGUYEN DUC THIEN,, et al.
出版: (2012)

Sample-efficient iterative lower bound optimization of deep reactive policies for planning in continuous MDPs
由: LOW, Siow Meng, et al.
出版: (2022)

Parameter Learning for Latent Network Diffusion
由: WU, Xiaojian, et al.
出版: (2013)

Constrained reinforcement learning in hard exploration problems
由: PATHMANATHAN, Pankayaraj, et al.
出版: (2023)

On forward pruning in game-tree search
由: LIM YEW JIN
出版: (2010)

Distributed Gibbs: A linear-space sampling-based DCOP algorithm
由: NGUYEN, Duc Thien, et al.
出版: (2019)

Probabilistic Analysis of Local Search and NP-Completeness Results for Constraint Satisfaction
由: LAU, Hoong Chuin
出版: (1996)

Collective Diffusion Over Networks: Models and Inference
由: KUMAR, Akshat, et al.
出版: (2013)

Automated Generation of Interaction Graphs for Value-Factored Decentralized POMDPs
由: YEOH, William, et al.
出版: (2013)

Lagrangian Relaxation Techniques for Scalable Spatial Conservation Planning
由: KUMAR, Akshat, et al.
出版: (2012)

Probabilistic Inference Techniques for Scalable Multiagent Decision Making
由: Akshat KUMAR,, et al.
出版: (2015)

AI-powered systems for scholarly search and content production
由: WANG, Lucy Lu
出版: (2024)

Incremental DCOP Search Algorithms for Solving Dynamic DCOP Problems
由: YEOH, William, et al.
出版: (2015)

Academic search and discovery tools in the age of AI and large language models: An overview of the space
由: TAY, Aaron
出版: (2024)

Learning and Controlling Network Diffusion in Dependent Cascade Models
由: DU, Jiali, et al.
出版: (2015)

Robust decision making for stochastic network design
由: Akshat KUMAR,, et al.
出版: (2016)

FlowPG: Action-constrained policy gradient with normalizing flows
由: BRAHMANAGE JANAKA CHATHURANGA THILAKARATHNA,, et al.
出版: (2023)

A balanced view of artificial intelligence
由: Ngo, Courtney Anne M.
出版: (2018)

Can we regulate artificial intelligence?
由: Javier, Cholo E.
出版: (2024)

How to think like an AI
由: Lugtu, Reynaldo C., Jr.
出版: (2024)

Is AI making us smarter or dumber?
由: Lugtu, Reynaldo C.
出版: (2024)

The rise of generation AI
由: Lugtu, Reynaldo C., Jr.
出版: (2025)

Teaching use of AI with meta-reflections
由: Aure, Patrick Adriel H.
出版: (2023)

Influence Diagrams With Memory States: Representation and Algorithms
由: WU, Xiaojian, et al.
出版: (2011)

An approach for self-training audio event detectors using web data
由: ELIZALDE, Benjamin, et al.
出版: (2017)

An Artificial Immune System based Approach for English Grammar Correction
由: KUMAR, Akshat, et al.
出版: (2007)

Combinatorial approaches for hard problems in manpower scheduling
由: LAU, Hoong Chuin
出版: (1996)

Manpower scheduling with shift change constraints
由: LAU, Hoong Chuin
出版: (1994)

Collective multiagent sequential decision making under uncertainty
由: NGUYEN, Duc Thien, et al.
出版: (2017)