1. Introduction to Artificial Intelligence – Unit 9 Wrap-up Course 67842
The Hebrew University of Jerusalem
School of Engineering and Computer Science
Instructor: Jeff Rosenschein

2. What This Course Covered
Intelligent Agents, What is AI?
Search
Knowledge Representation
Planning
Learning
Game Theory

3. More Detailed Structure
Introduction: what is AI? the Turing Test; History of AI; state of the art
Intelligent Agents: rationality, environments, agent structure
Search: breadth-first, depth-first, iterative deepening, bidirectional search, informed heuristic search, A*, heuristic functions, hill climbing, simulated annealing, Constraint satisfaction problems, backtracking search for CSPs, Adversarial search, games, minimax, alpha-beta pruning

4. More Detailed Structure 2
Knowledge Representation: propositional logic; propositional inference, first-order logic; quantifiers; encoding of knowledge, inference in first-order logic, unification, forward chaining, backward chaining, resolution
Planning: planning with state-space search, partial order planning, planning graphs, planning with propositional logic, hierarchical task network planning, conditional planning, continuous planning, multiagent planning

5. More Detailed Structure 3
Learning: Markov Systems, Markov Decision Problems (MDPs), Partially Observable Markov Decision Problems (POMDPs), reinforcement learning, learning from observations, learning decision trees
Game Theory: zero-sum game theory, non- zero sum game theory, auctions, voting, manipulation, coalitions and coalitional power

6. AI: A Dynamic Field
There are many ways of categorizing approaches to problems in AI
Neat vs. Scruffy
Theoreticians vs. Experimentalists
Rule-based vs. data-based
Users of particular “tools” or “approaches”
POMDPs
Learning
And more…

7. What are the State-of-the-Art Research Topics?
IJCAI’13 met in Beijing, China, August 2013
Session topics and Number of Papers
Agent-based and Multiagent Systems: 58
Constraints, Satisfiability, and Search: 35
Knowledge Representation, Reasoning, and Logic: 73
Machine Learning: 106
Multidisciplinary Topics and Applications: 13
Natural Language Processing: 28
Planning and Scheduling: 28
Robotics and Vision: 8
Uncertainty in AI: 10
Web and Knowledge-based Information Systems: 26

8. Sample Paper Titles, IJCAI’13
Agent-based and Multiagent Systems
How to Change a Group’s Collective Decision?
Constraints, Satisfiability, and Search
Preserving Partial Solutions while Relaxing Constraint Networks
Knowledge Representation, Reasoning, and Logic
First-Order Expressibility and Boundedness of Disjunctive Logic Programs
Machine Learning
Central Clustering of Categorical Data with Automated Feature Weighting

9. What are the AI Apps to Come?
Long-held dreams are coming true:
Speech Recognition
Language Translation
Autonomous Driving
Mundane tasks made possible by learning from data:
FareCast
What would we want a machine to do, that it can’t do now?
Teaching?
Home care (robotics)?

10. Fears about AI
Elon Musk (Paypal, SpaceX, Tesla): Artificial Intelligence is “potentially more dangerous than nukes…I think we should be very careful about artificial intelligence. If I had to guess at what our biggest existential threat is, it’s probably that. So we need to be very careful. I’m increasingly inclined to think that there should be some regulatory oversight, maybe at the national and international level, just to make sure that we don’t do something very foolish.”

11. Fears about AI
Physicist Stephen Hawkings: “AI could be a big danger in the not-too-distant future…The development of full artificial intelligence could spell the end of the human race”
Etzioni: “the emergence of ‘full artificial intelligence’ over the next twenty-five years is far less likely than an asteroid striking the earth and annihilating us.”

12. Responses
Oren Etzioni: “I am an AI researcher and I’m not scared. Here’s why.”
Confusion between “intelligence” and “autonomy”
“autonomous computer programs exist and some are scary — such as viruses or cyber-weapons. But they are not intelligent. And most intelligent software is highly specialized; the program that can beat humans in narrow tasks, such as playing Jeopardy, has zero autonomy. IBM’s Watson is not champing at the bit to take on Wheel of Fortune next. Moreover, AI software is not conscious. As the philosopher John Searle put it, ‘Watson doesn’t know it won Jeopardy!’”

13. Responses
Dietterich and Horvitz: ״Benefits and Risks of Artificial Intelligence״
The Real risks:
Software quality: developing and validating software to high levels of quality assurance
Cyberattacks against critical software
“Sorcerer’s Apprentice”: Software that integrates well with humans: understanding context, transfering control
The first two are true of software in general

14. AI (and Software) Ethical Issues
When computers are programmed to take the place of humans, where does liability reside?
Is fast behavior unethical, when slow versions of the same behavior are ethical (e.g., machine scanning of vast amounts of mortgage information, publically available, that would be much harder to analyze if done by a human)?
Human-machine symbiosis – what crosses the line?
Machine-machine behavior – is any behavior that is unethical for humans allowed for computers? Vice versa?

15. Good Luck with Your Final Quiz, and with your Projects!