'Reward model' presentation slideshows

Intelligent Systems (AI-2) Computer Science cpsc422 , Lecture 8 Jan, 22, 2014

Intelligent Systems (AI-2) Computer Science cpsc422 , Lecture 8 Jan, 22, 2014. Course Announcements. Assignment 1 has been posted ValueOfInfo and ValueOfControl MDPs: Value Iteration POMDPs: Belief State Update. Lecture Overview. Finish Q-learning Algorithm Summary Example.

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Honeywell Laboratories

Coordinator. Autonomy. Organization. Coordination. Meta. Task Analysis. Change. Honeywell Laboratories. Coordination of Highly Contingent Plans. David Musliner Ed Durfee, Jianhui Wu, Dmitri Dolgov Robert Goldman Mark Boddy. Outline. Problem overview: Coordinators, C-TAEMS.

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Intelligent Systems (AI-2) Computer Science cpsc422 , Lecture 7 Jan, 20, 2014

Intelligent Systems (AI-2) Computer Science cpsc422 , Lecture 7 Jan, 20, 2014. Lecture Overview. Finish POMDPs Look ahead Applications. Start Reinforcement Learning Start Q-learning. Look Ahead Search for Optimal Policy.

471 views • 38 slides

Disease Management & Pay-for-Performance: Is it just about the money?

Disease Management & Pay-for-Performance: Is it just about the money?. June 22, 2005. Harry L. Leider, MD, MBA Chief Medical Officer, XLHealth. Disease Management & Health Outcomes, Dec. 6 th , 1999. DM P4P Experience. Real World Experience in P4P. CardioContinuum

421 views • 28 slides

Helping and Happiness

Helping and Happiness. Altruism vs. Prosocial behavior Why do people help? http://www.msnbc.msn.com/id/43880728/ns/world_news-europe/ http://www.smh.com.au/world/it-was-too-dark-passersby. Evolutionary approaches to prosocial behavior. Kin altruism Direct reciprocity

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Altruism and Aggression

Altruism and Aggression. Chapter 8. Class Exercise & Discussion. List three occasions when you helped another person. What were your motives for helping the person on each occasion?. HELPING and ALTRUISM. 1. Motivation to Help Others 2. Characteristics of Needy -> Helping

1.28k views • 20 slides

Reinforcement learning

Svetlana Lockwood Washington State University CptS 540 Fall 2010. Reinforcement learning . Background. Dates back to the early days of cybernetics. Goal : to program agents by reward and punishment without needing to specify how the task is to be achieved. BUT

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Section 8: Markov Decision Process

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