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Observable
Results: 793

#	Item
101	Learning Partially Observable Action Schemas Dafna Shahaf and Eyal Amir Computer Science Department University of Illinois, Urbana-Champaign Urbana, IL 61801, USA {dshahaf2,eyal}@uiuc.edu Add to Reading List Source URL: i.stanford.edu Language: English - Date: 2010-08-28 23:41:11
102	Evaluation of Statistical POMDP-based Dialogue Systems in Noisy Environments Steve Young, Catherine Breslin, Milica Gaˇsi´c, Matthew Henderson, Dongho Kim, Martin Szummer, Blaise Thomson, Pirros Tsiakoulis, Eli Tzirkel Add to Reading List Source URL: mi.eng.cam.ac.uk Language: English - Date: 2014-06-03 16:14:30 Statistics Human–computer interaction User interfaces Machine translation Speech recognition Partially observable Markov decision process Usability Speech synthesis Dialog system Humanâ€“computer interaction Computational linguistics Science
103	Read what people are saying about Why We Disagree About Climate Change The Economist, 4 December 2009 - “How global warming has been transformed from a physical phenomenon that is measurable and observable by scientist Add to Reading List Source URL: mikehulme.org Language: English - Date: 2010-02-17 13:20:51 Books Why We Disagree About Climate Change Global warming Mike Hulme Environmental skepticism Global warming controversy Copenhagen Climate Council Climate change Environment Climatology
104	AAAI Proceedings Template Add to Reading List Source URL: mi.eng.cam.ac.uk Language: English - Date: 2005-06-16 09:47:36 Stochastic control Control theory Partially observable Markov decision process Markov decision process Reinforcement learning Dialogue FO Usability Statistics Dynamic programming Markov processes
105	Scaling Up POMDPs for Dialog Management: The “Summary POMDP” Method Jason D. Williams and Steve Young Cambridge University Engineering Department Trumpington Street, Cambridge CB2 1PZ, UK . Add to Reading List Source URL: mi.eng.cam.ac.uk Language: English - Date: 2005-07-01 06:49:10 Stochastic control Control theory User interfaces Partially observable Markov decision process Dialog system Markov decision process Dialogue Mode Statistics Dynamic programming Markov processes
106	Learning Partially Observable Action Models: Efficient Algorithms Dafna Shahaf Allen Chang Eyal Amir Computer Science Department University of Illinois, Urbana-Champaign Urbana, IL 61801, USA {dshahaf2,achang6,eyal}@uiuc Add to Reading List Source URL: infolab.stanford.edu Language: English - Date: 2010-08-28 23:41:19 Logic in computer science Logic programming Automated planning and scheduling Formal methods Conjunctive normal form Situation calculus Planning Domain Definition Language Algorithm Boolean satisfiability problem Theoretical computer science Mathematics Applied mathematics
107	ON-LINE POLICY OPTIMISATION OF BAYESIAN SPOKEN DIALOGUE SYSTEMS VIA HUMAN INTERACTION M. Gaˇsi´c, C. Breslin, M. Henderson, D. Kim, M. Szummer, B. Thomson, P. Tsiakoulis and S. Young Cambridge University Engineering De Add to Reading List Source URL: mi.eng.cam.ac.uk Language: English - Date: 2012-11-29 17:55:40 Stochastic control Bayesian statistics Partially observable Markov decision process Simulation Gaussian process Dialogue Markov decision process Machine learning Supervised learning Statistics Dynamic programming Markov processes
108	Exact computations with approximate arithmetic Add to Reading List Source URL: perso.ens-lyon.fr Language: English - Date: 2007-10-26 06:17:09 Computing Floating point P5 Division Observable universe Multiplication Cray Computer Software bug Computer arithmetic Mathematics Numbers
109	Towards a Principled General Approach to Motion Planning under Uncertainty David Hsu National University of Singapore Add to Reading List Source URL: www.cse.unr.edu Language: English - Date: 2012-12-20 19:29:32 Control theory Robot Motion Mathematical sciences Motion planning Cybernetics Index of robotics articles Dynamic programming Partially observable Markov decision process Stochastic control
110	Reusable Sampling-Based Techniques for Manipulation via Pushing Christopher Vo Abstract—In this work, we consider the problem of manipulating a polygonal object through an obstacle-filled environment using only push in Add to Reading List Source URL: www.cse.unr.edu Language: English - Date: 2012-12-20 19:29:59 Theoretical computer science Kinodynamic planning International Conference On Intelligent Robots and Systems Partially observable Markov decision process Robot ROS Cognitive robotics Robotics Robot kinematics Motion planning

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