'Credit assignment' presentation slideshows

Reinforcement Learning

Reinforcement Learning. Based on slides by Avi Pfeffer and David Parkes. Mechanism. State. Closed Loop Interactions. Environment. Reward. Agent. Sensors. Actuators. Percepts. Actions. Reinforcement Learning. When mechanism(=model) is unknown

794 views • 68 slides

Flexible Reasoning with Functional Models

Flexible Reasoning with Functional Models. J. William Murdock Intelligent Decision Aids Group Navy Center for Applied Research in Artificial Intelligence Naval Research Laboratory, Code 5515 Washington, DC 20375 bill@murdocks.org http://bill.murdocks.org.

607 views • 51 slides

8/27

476 views • 47 slides

Administrivia/Announcements

418 views • 40 slides

Distributed Network Coding Based Opportunistic Routing for Multicast

Distributed Network Coding Based Opportunistic Routing for Multicast. Abdallah Khreishah, Issa Khalil , and Jie Wu. Enhancing the Performance of Wireless Networks. Why to study the problem?

562 views • 35 slides

Universal Opportunistic Routing Scheme using Network Coding

Universal Opportunistic Routing Scheme using Network Coding. Abdallah Khreishah, Issa Khalil , and Jie Wu. Enhancing the Performance of Wireless Networks. Why to study the problem? Wireless multihop networks are becoming integral part of our lives. (Mesh networks, sensor networks, etc..)

697 views • 30 slides

Design Principles for Creating Human-Shapable Agents

Design Principles for Creating Human-Shapable Agents. W. Bradley Knox, Ian Fasel, and Peter Stone. The University of Texas at Austin Department of Computer Sciences. Transferring human knowledge through natural forms of communication. Potential benefits over purely autonomous learners:

243 views • 24 slides

GAME PLAYING

GAME PLAYING. Every game of skill is susceptible of being played by an automaton. - Charles Babbage (1791-1871), English mathematician, philosopher, inventor and mechanical engineer OVERVIEW

392 views • 23 slides

CS344: Introduction to Artificial Intelligence

CS344: Introduction to Artificial Intelligence. Pushpak Bhattacharyya CSE Dept., IIT Bombay Lecture 17: Feedforward network: non linear separability 9 th Feb, 2012. # of Threshold functions n # Boolean functions (2^2^n) #Threshold Functions (2 n2 ) 1 4 4 2 16 14

242 views • 17 slides

CS344: Introduction to Artificial Intelligence

CS344: Introduction to Artificial Intelligence. Pushpak Bhattacharyya CSE Dept., IIT Bombay Lecture 18,19: Sigmoid neuron 13 th and 14 th Feb , 2012. FFNN Example- XOR. = 0.5. w 1 =1. w 2 =1. ? Calculation of XOR. x 1 x 2. x 1 x 2. Calculation of . x 1 x 2. = 1. w 1 =-1.

256 views • 16 slides