Reinforcement Learning

• Learning an optimal strategy for maximizing future reward
• Agent has little prior knowledge and no immediate feedback
• Action credit assignment difficult when only future reward
• Two basic agent designs
  • Agent learns utility function $U(i)$ on states
  • Agent learns action-value function
• Can handle deterministic or probabilistic state transitions