History, state of the art, Need for AI in Robotics. Thinking and acting humanly, intelligent agents, structure of agents. PROBLEM SOLVING: Solving problems by searching –Informed search and exploration–Constraint satisfaction problems–Adversarial search, knowledge and reasoning–knowledge representation –first order logic.

Planning with forward and backward State space search –Partial order planning –Planning graphs–Planning with propositional logic –Planning and acting in real world

Uncertainty –Probabilistic reasoning–Filtering and prediction–Hidden Markov models–Kalman filters–Dynamic Bayesian Networks, Speech recognition, making decisions.

Forms of learning –Knowledge in learning –Statistical learning methods –reinforcement learning, communication, perceiving and acting, Probabilistic language processing, perception.

Robotic perception, localization, mapping-configuring space, planning uncertain movements, dynamics and control of movement, Ethics and risks of artificial intelligence in robotics.