1. CS382 Introduction to Artificial Intelligence Lecture 1: The Foundations of AI and Intelligent Agents 24 January 2012 Instructor: Kostas Bekris Computer Science & Engineering, University of Nevada, Reno

2. 382 What is AI? “The automation of activities that we associate with human thinking, activities such as decision-making, problem solving, learning” (Bellman, 1978) “The study of mental faculties through the use of computational models.” (Winston, 1992) “The art of creating machines that perform functions that require intelligence when performed by people” (Kurzweil, 1990) “AI is concerned with rational action... and studies the design of rational agents. A rational agent acts so as to achieve the best expected outcome” (S.R. & P.N., 1995) HumanlyRationallyvs. Thinking Acting vs.

3. 382 What is AI? “The automation of activities that we associate with human thinking, activities such as decision-making, problem solving, learning” (Bellman, 1978) “The study of mental faculties through the use of computational models.” (Winston, 1992) “The art of creating machines that perform functions that require intelligence when performed by people” (Kurzweil, 1990) “AI is concerned with rational action... and studies the design of rational agents. A rational agent acts so as to achieve the best expected outcome” (S.R. & P.N., 1995) HumanlyRationallyvs. Thinking Acting vs.

4. 382 Acting Humanly

5. 382 What is AI? “The automation of activities that we associate with human thinking, activities such as decision-making, problem solving, learning” (Bellman, 1978) “The study of mental faculties through the use of computational models.” (Winston, 1992) “The art of creating machines that perform functions that require intelligence when performed by people” (Kurzweil, 1990) “AI is concerned with rational action... and studies the design of rational agents. A rational agent acts so as to achieve the best expected outcome” (S.R. & P.N., 1995) HumanlyRationallyvs. Thinking Acting vs.

6. 382 Thinking Humanly

7. 382 What is AI? “The automation of activities that we associate with human thinking, activities such as decision-making, problem solving, learning” (Bellman, 1978) “The study of mental faculties through the use of computational models.” (Winston, 1992) “The art of creating machines that perform functions that require intelligence when performed by people” (Kurzweil, 1990) “AI is concerned with rational action... and studies the design of rational agents. A rational agent acts so as to achieve the best expected outcome” (S.R. & P.N., 1995) HumanlyRationallyvs. Thinking Acting vs.

8. 382 Thinking Rationally

9. 382 What is AI? “The automation of activities that we associate with human thinking, activities such as decision-making, problem solving, learning” (Bellman, 1978) “The study of mental faculties through the use of computational models.” (Winston, 1992) “The art of creating machines that perform functions that require intelligence when performed by people” (Kurzweil, 1990) “AI is concerned with rational action... and studies the design of rational agents. A rational agent acts so as to achieve the best expected outcome” (S.R. & P.N., 1995) HumanlyRationallyvs. Thinking Acting vs.

10. 382 Acting Rationally

11. 382

12. Where are we now?

13. 382 Intelligent Agents

14. 382 Environments and their properties

15. 382 Environments and their properties

16. 382 How do agents work?

17. 382 Reflex Agents

18. 382 Model-based Reflex Agents

19. 382 Goal-based Agents

20. 382 Utility-based Agents

21. 382 Learning Agents

22. 382 Structure of the Course Part 1. Decision-Making in Deterministic Environments Single-agent: Dynamic programming and search, informed search and heuristics, randomized search, constraint satisfaction Multi-agent: Adversarial search (mini-max and expecti-mini-max) Part 2. Decision-Making in Stochastic Environments Single-agent: Bayesian networks, Hidden Markov Models, Kalman and Particle filters, Decision and Utility theory, (Partially Observable) Markov Decision Processes Multi-agent: Introduction to Game Theory Part 3. Introduction to Robotics, Vision and Bio-Inspired AI Search in continuous spaces, behaviors, image processing and understanding, genetic algorithms and neural networks

23. 382 What are my personal interests? Agents that must and do appropriately model and reason about the physical properties of their environment: algorithmic generation of motion (motion planning) state estimation problems given noisy sensors and distributed message-passing coordination Physicall y- Grounde d Agents Robotics Computer Games Human Assistants