Back to Results
First PageMeta Content
Dynamic programming / Markov processes / Stochastic control / Operations research / Equations / Markov decision process / A* search algorithm / Automated planning and scheduling / Mathematical optimization / Statistics / Mathematics / Control theory


Planning for Markov Decision Processes with Sparse Stochasticity Maxim Likhachev School of Computer Science Carnegie Mellon University
Add to Reading List

Document Date: 2005-01-16 14:16:52


Open Document

File Size: 683,25 KB

Share Result on Facebook

City

Cambridge / Palo Alto / /

Company

Neural Information Processing Systems / MIT Press / Tioga Publishing / /

/

Facility

Computer Science Carnegie Mellon University / building M / Carnegie Mellon University / /

IndustryTerm

search method / search function / level algorithm / slower algorithms / search returns / stochastic planning algorithms / deterministic search / classical algorithms / overall algorithm / heuristic search algorithm / search algorithm / search iteration / deterministic search subroutine / search removes / deterministic search algorithm / /

Organization

MIT / Geoff Gordon School of Computer Science Carnegie Mellon University Pittsburgh / Stanford University / Sparse Stochasticity Maxim Likhachev School of Computer Science Carnegie Mellon University Pittsburgh / Carnegie Mellon University / Pittsburgh / /

Person

Sebastian Thrun / /

/

ProvinceOrState

Pennsylvania / /

Technology

outer MCP algorithm / laser / three algorithms / heuristic search algorithm / stochastic planning algorithms / 2 The Algorithm Our algorithm / overall algorithm / artificial intelligence / search algorithm / deterministic search algorithm / 94305 thrun@stanford.edu Abstract Planning algorithms / planning algorithm / simulation / 4 Discussion The MCP algorithm / MCP algorithm / slower algorithms / /

SocialTag