'Action models' presentation slideshows

Learning Action Models for Planning

Learning Action Models for Planning. Qiang Yang Department of Computer Science, Hong Kong University of Science and Technology, Hong Kong, China http://www.cse.ust.hk/~qyang. My students Junfeng Pan, Jie Yin, Dou Shen, Jialin Pan, Dr. Rong Pan, Kangheng Wu My sponsors Hong Kong RGC

820 views • 66 slides

CS 440 / ECE 448 Introduction to Artificial Intelligence Spring 2010 Lecture #3

734 views • 56 slides

587 views • 49 slides

Cross-Domain Action-Model Acquisition for Planning viaWeb Search

Cross-Domain Action-Model Acquisition for Planning viaWeb Search. Hankz Hankui Zhuo a , Qiang Yang b , Rong Pan a and Lei Li a a Sun Yat-sen University, China b Hong Kong University of Science & Technology, Hong Kong. Motivation.

561 views • 43 slides

Activity Recognition

Activity Recognition. Ram Nevatia Presents work of F. Lv, P. Natarajan and V. Singh Institute of Robotics and Intelligent Systems Computer Science Department Viterbi School of Engineering University of Southern California. Activity Recognition: Motivation.

752 views • 36 slides

CHAPTER 2: Guidelines, Principles, and Theories

Designing the User Interface: Strategies for Effective Human-Computer Interaction Fifth Edition Ben Shneiderman & Catherine Plaisant in collaboration with Maxine S. Cohen and Steven M. Jacobs. CHAPTER 2: Guidelines, Principles, and Theories. Guidelines. Shared language Best practices

472 views • 33 slides

CHAPTER 2: Guidelines, Principles, and Theories

Designing the User Interface: Strategies for Effective Human-Computer Interaction Fifth Edition Ben Shneiderman & Catherine Plaisant in collaboration with Maxine S. Cohen and Steven M. Jacobs. CHAPTER 2: Guidelines, Principles, and Theories. Guidelines. Shared language Best practices

479 views • 33 slides

Learning Integrated Symbolic and Continuous Action Models

Learning Integrated Symbolic and Continuous Action Models. Joseph Xu & John Laird May 29, 2013. Action Models. Definition of Action Model is world state at time , is action Long-living agents must adapt to new environments Must learn action models from observation. ?. Benefits.

334 views • 32 slides

Self-Improving Reactive Agents Based On Reinforcement Learning, Planning and Teaching

Self-Improving Reactive Agents Based On Reinforcement Learning, Planning and Teaching. By Long-Ji Lin, Carnegie Mellon University 1992 Presented By Jonathon Marjamaa February 16, 2000. Overview. AHC-learning: Framework AHCON Q-Learning: Framework QCON

392 views • 26 slides

Self-Improving Reactive Agents Based On Reinforcement Learning, Planning and Teaching

Self-Improving Reactive Agents Based On Reinforcement Learning, Planning and Teaching. By Long-Ji Lin, Carnegie Mellon University 1992 Presented By Jonathon Marjamaa February 16, 2000. Overview. AHC-learning: Framework AHCON Q-Learning: Framework QCON

273 views • 26 slides

Long-term Employment for the Disabled

Long-term Employment for the Disabled. The Region of Vorarlberg. Vorarlberg, the westernmost state of Austria at Lake Constance, borders the Tyrol, Germany, Switzerland and the Principality of Liechtenstein. 2,601 km 2. Population + Economy. 380,000 inhabitants

299 views • 21 slides

Learning HTN Method Preconditions and Action Models from Partial Observations

Learning HTN Method Preconditions and Action Models from Partial Observations. Hankz Hankui Zhuo a , Derek Hao Hu a , Chad Hogg b , Qiang Yang a and Hector Munoz-Avila b a: Hong Kong University of Science & Technology, b: Lehigh University. Motivation.

265 views • 17 slides

Action Modeling with Graph-Based Version Spaces in Soar

331 views • 17 slides

Learning Applicability Conditions in AI Planning from Partial Observations

Learning Applicability Conditions in AI Planning from Partial Observations. Hankz Hankui Zhuo a , Derek Hao Hu a , Chad Hogg b , Qiang Yang a and Hector Munoz-Avila b a: Hong Kong University of Science & Technology, b: Lehigh University. Motivation.

247 views • 16 slides

Learning, Recognizing, and Assisting with Activities

Learning, Recognizing, and Assisting with Activities. Tom Dietterich Oregon State University. Assumptions. Goal: Integrated, autonomous, and useful AI systems Must collaborate well with people Must recognize and understand human goals, attentional state, costs of coordination, etc.

169 views • 15 slides