People:
 Learning, perception and action
 Machine learning
 Neuroscience
 Robots
 Autonomous robots  how do we make things that work? (Robotic systems, theory/algorithms, neuro studies)
 Modular planning
 Teaching and imitation
 Trial and error learning
 Interaction with the environment
 Learning control
 Multimodal perception
 Movement primitives
 Control policy
 Dynamic movement primitives are solved by producing attractor/repeller dynamics
 Trial error (reinforcement learning)
 Algorithm
 Teach with imitation
 Provide an objective function
 Perform trial and error to explore space
 Reinforcement learning
 Policy
 Reward function
 Value function
 Model
 What do people do?
 Statebased
 Trajectorybased
 Scalable to highdimensions
 Pathintegral Reinforcement Learning
 Take affine system dynamics
 Have stochasitc cost function
 Try and solve stochastic HJB
 Use magic logtransform trick
 Squash reward into weight from zerotoone, apply weight
 Apply feynmankac theorem (allows empirical evaluation)
 Generate optimal control policy
 Adapting to dynamically changing world
 Hoffmann ICRA 2009
 Pastor IROS 2011
 Learning control with internal models
 Associative skill memories
 Action is associated with all perceptual information
 Success vs failure detection based on associating sensory info to actions that allow prediction of next action
