PPT-CS 4700: Foundations of Artificial Intelligence

Bart Selman selmancscornelledu Module Knowledge Reasoning and Planning Part 1 Logical Agents RampN Chapter 7 A ModelBased Agent Requires Knowledge and Reasoning Knowledge and Reasoning . Movies… anyone?. What should I do?. Tell me SOMETHING. Being more formal. Artificial Intelligence is something which gives computers the ability to learn without. b. eing explicitly programmed. Current state of machine intelligence. Presented . by. :. . . Oliwual. . Islam. . . Vivek. . Mishra. . . Rahul. . Ravish. . Bart Selman. selman@cs.cornell.edu. Logical Agents --- . Intro Knowledge Representation. & Boolean Satisfiability (SAT) encodings. R&N: Chapter 7. A Model-Based Agent. Requires: Knowledge and Reasoning. Bart Selman. selman@cs.cornell.edu. Module: Knowledge, Reasoning, and Planning. Logical Agents. Model . Theoretic Semantics. Entailment . and Proof Theory. R&N: Chapter 7. Logical agents:. . . Bart Selman. Search Techniques. R&N: Chapter 3. Outline. Search: tree search and graph search. Uninformed. . search: very briefly (covered before in other pre-requisite courses – recommendation: review these techniques at home). Bart Selman. selman@cs.cornell.edu. Module: . Adversarial Search . R&N: Chapter 5. Outline. Adversarial Search . Optimal decisions. Minimax. α-β pruning. Case study: Deep Blue. UCT and Go. Adversarial Reasoning: Games. Bart Selman. selman@cs.cornell.edu. Module: Knowledge, Reasoning, and Planning. First-Order Logic and Inference. R&N: Chapters 8 and 9. Finite domains === “essentially propositional.” Also called:. Nick . Deheck. Chelsey . Eglseder. Joshua Lewis. David Summey. What is Artificial Intelligence? . Simulation of human intelligence. "Alexa"; "Watson. ". Machines learn from experience. Netflix. Ability to adjust to new inputs and perform human-like tasks. What impact might it have on how we work and live? What opportunities does it present for independent schools? . Understanding Artificial Intelligence. (AI). SAS.com. AI makes it possible for machines to learn from experience, adjust to new inputs, and perform human-like tasks.. and. . Machine Learning H. elp Create a . Military. . Operational Advantage?. . Offset Symposium. April 18-19, 2018. George Galdorisi. Strategic Assessments and Technical Futures Group. SPAWAR Systems Center Pacific. to . rscheearch. at . Cmabrigde. . Uinervtisy. , it . deosn't. . mttaer. in . waht. . oredr. the . ltteers. in a . wrod. are, the . olny. . iprmoatnt. . tihng. is . taht. the . frist. and . Bart Selman. selman@cs.cornell.edu. Informed Search . Readings R&N - Chapter 3: 3.5 and 3.6. Search. Search strategies determined by choice of node (in queue) to expand. Uninformed. search:. Distance to goal not taken into account. Prof. Bart Selman. selman@cs.cornell.edu. Machine Learning:. Decision . Trees. R&N 18.3. Big Data:. Sensors Everywhere. Data collected and stored at . enormous speeds (GB/hour. ). Cars. Cellphones. (. AI). , sometimes known as machine intelligence, refers . to the ability of computers to perform human-like feats of cognition including learning, problem-solving, perception, decision-making, and speech and language..