Satinder Singh
homepage:http://www.eecs.umich.edu/~baveja/
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Description

My main research interest is in the old-fashioned goal of Artificial Intelligence (AI), that of building autonomous agents that can learn to be broadly competent in complex, dynamic, and uncertain environments. The field of reinforcement learning (RL) has focused on this goal and accordingly my deepest contributions are in RL.

More recently, I have been taking seriously the challenge of building agents that can interact with other agents and even humans in both artificial and natural environments. This has led to research in:

  • human-computer interaction
  • computational game theory
  • mechanism design


Lectures:

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tutorial
flag Reinforcement Learning
as author at  Machine Learning Summer School (MLSS), Canberra 2006,
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votesvotesvotesvotesvotes [syn]  14854 views, 1:24:39  
lecture
flag Reinforcement learning: Tutorial + Rethinking State, Action & Reward
as author at  Cognitive Science and Machine Learning Summer School (MLSS), Sardinia 2010,
14854 views
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lecture
flag Reinforcement Learning
as author at  Deep Learning (DLSS) and Reinforcement Learning (RLSS) Summer School, Montreal 2017,
5641 views
 
[syn]  4507 views, 28:04  
lecture
flag Efficiently Learning Linear-Linear Exponential Family Predictive Representations of State
as author at  Reinforcement Learning,
4507 views
[syn]  1620 views, 28:04  
opening
flag Welcome and Opening Remarks
as presenter at  31st AAAI Conference on Artificial Intelligence, San Francisco 2017,
together with: Thomas G. Dietterich (presenter), Ashok Goel (presenter), G. Michael Youngblood (presenter), Shaul Markovitch (presenter),
1620 views