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Problem-solving methods in artificial intelligence

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Problem Solving Methods in Artificial Intelligence Hardcover – Import, January 1, 1971

• Print length 256 pages
• Language English
• Publisher McGraw-Hill
• Publication date January 1, 1971
• ISBN-10 0070465738
• ISBN-13 978-0070465732
• See all details

Product details

• Publisher ‏ : ‎ McGraw-Hill; First Edition (January 1, 1971)
• Language ‏ : ‎ English
• Hardcover ‏ : ‎ 256 pages
• ISBN-10 ‏ : ‎ 0070465738
• ISBN-13 ‏ : ‎ 978-0070465732
• Item Weight ‏ : ‎ 1.3 pounds
• #3,852 in Decision-Making & Problem Solving

About the author

Nils john nilsson.

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Nils J. Nilsson - Publications

Books | Contributions to Books | Archival Journal Articles | Conference Proceedings

Refereed Conference Proceedings | Essays | Other Writings | Home page

Nilsson, N., Learning Machines: Foundations of Trainable Pattern-Classifying Systems , New York: McGraw-Hill, 1965. (Reprinted as: Nilsson, N., The Mathematical Foundations of Learning Machines , San Francisco: Morgan Kaufmann, 1990.)

Nilsson, N., Problem-Solving Methods in Artificial Intelligence , New York: McGraw-Hill, 1971.

Nilsson, N., Principles of Artificial Intelligence , San Francisco: Morgan Kaufmann, 1980.

Webber, B., and Nilsson, N., (eds.), Readings in Artificial Intelligence , San Francisco: Morgan Kaufmann, 1981.

Genesereth, M., and Nilsson, N., Logical Foundations of Artificial Intelligence , San Francisco: Morgan Kaufmann, 1987.

Nilsson, N., Artificial Intelligence: A New Synthesis , San Francisco: Morgan Kaufmann, 1998. (For a list of known errors and typos, see Errata. . Also, check out some Clarifications .)

Nilsson, N., The Quest for Artificial Intelligence: A History of Ideas and Achievements , Cambridge University Press , 2010.

Nilsson, N., Understanding Beliefs , The MIT Press, 2014.

My draft book on Machine Learning is still available on the web even though it is becoming outdated.

Books | Contributions to Books | Archival Journal Articles | Conference Proceedings | Refereed Conference Proceedings | Essays | Other Writings | Home page

Contributions to Books

Block, H., Duda, R., and Nilsson, N., "Determination and Detection of Features in Patterns," in Computer and Information Sciences , pp. 75-110, Washington, DC: Spartan Books, Inc., 1964. Available as an optically scanned report , December 1963.

Nilsson, N., and Raphael, B., "Preliminary Design of an Intelligent Robot," in Tou, J. T., (ed.), Computer and Information Sciences II , pp. 235-259, New York: Academic Press, 1967.

Arbib, M., Nilsson, N., and Franklin, G., "Some Ideas on Information Processing in the Cerebellum," in Caianiello, E. R. (ed.), Neuronal Networks , pp. 43-58, New York: Springer, 1968.

Nilsson, N., "Adaptive Pattern Recognition: A Survey," in Cybernetic Problems in Bionics , New York: Gordon and Breach Science Publishers, Inc., 1968.

Fikes, R., Hart, P., and Nilsson, N., "Some New Directions in Robot Problem Solving," in Meltzer, B., and Michie, D. (eds.), Machine Intelligence 7 , pp. 405-430, Edinburgh: Edinburgh University Press, 1972. Available as an SRI AI Center Technical Note (No. 68) .

Nilsson, N., "Robots and Artificial Intelligence," Encyclopedia of Modern Science , Kodansha Publishing Co., 1973.

Duda, R., Hart, P., Nilsson, N., and Sutherland, G., "Semantic Network Representations in Rule-based Inference Systems," in Waterman, D., and Hayes-Roth, R., (eds.), Proceedings of a Workshop on Pattern-Directed Inference Systems , Hawaii, May 1977. Available as an SRI AI Center Technical Note (No. 136) .

Nilsson, N., "A Production System for Automatic Deduction," in Elcock and Michie (eds.), Machine Intelligence 9 , Edinburgh: Edinburgh University Press, 1979. Available as an SRI AI Center Technical Note (No. 148) .

Duda, R. O., Nilsson, N. J., and Raphael, B., "State of Technology in Artificial intelligence," in P. Wegner (ed.), Research Directions in Software Technology , Cambridge, MA: MIT Press, pp. 729-749, 1980.

Nilsson, N., "Artificial Intelligence, Employment, and Income," Chapter 9 (pages 103-123) of Impacts of Artificial Intelligence: Scientific, Technological, Military, Economic, Societal, Cultural, and Political , Robert Trappl and Michael A. Arbib (Eds.), North-Holland, 1986.

Benson, S., and Nilsson, N., " Reacting, Planning and Learning in an Autonomous Agent ," in Furukawa, K., Michie, D., and Muggleton, S. (eds.), Machine Intelligence 14 , Oxford: The Clarendon Press, 1995. (In connection with this article, also see the draft memo by Benson and Nilsson entitled " Reactive Architecture Memo ." It deals with the matter of how best to choose from among a number of goals to achieve.)

Nilsson, N., " The Physical Symbol System Hypothesis: Status and Prospects ," in M. Lungarella, et al., (eds.), 50 Years of AI, Festschrift , LNAI 4850, pp. 9-17, Springer, 2007.

Archival Journal Articles

Nilsson, N., " On the Optimum Range Resolution of Radar Signals in Noise ", IRE Transactions on Information Theory , October, 1961.

Hart, P., Nilsson, N., and Raphael, B., " A Formal Basis for the Heuristic Determination of Minimum Cost Paths ," IEEE Trans. Syst. Science and Cybernetics , SSC-4(2):100-107, 1968.

Hart, P., Nilsson, N., and Raphael, B., " Correction to 'A Formal Basis for the Heuristic Determination of Minimum-Cost Paths' ," SIGART Newsletter , no. 37, pp. 28-29, December, 1972.

Fikes, R., and Nilsson, N., " STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving ," Artificial Intelligence , 2(3/4):189-208, 1971.

Luckham, D. C. and Nilsson, N., " Extracting Information from Resolution Proof Trees ," Artificial Intelligence , 2(1):27-54, 1971.

Fikes, R., Hart, P., and Nilsson, N., " Learning and Executing Generalized Robot Plans ," Artificial Intelligence , 3(4):251-288, 1972. ( Online version available, as an SRI Technical Note .)

Nilsson, N., "The Interplay Between Experimental and Theoretical Methods in Artificial Intelligence," Cognition and Brain Theory , January 1981. A draft version exists as an SRI AI Center Technical Note, Nils J. Nilsson, " The Interplay Between Experimental and Theoretical Methods in Artificial Intelligence ," SRI AI Center Technical Note 229, September, 1980.

Nilsson, N., " Probabilistic Logic ," Artificial Intelligence , 28(1):71-87, 1986.

Nilsson, N. " Logic and Artificial Intelligence ," Artificial Intelligence , 47:31-56, 1991.

Nilsson, N., " Probabilistic Logic Revisited ," Artificial Intelligence , vol. 59, pp. 39-42, 1993.

Fikes, R., and Nilsson, N., " STRIPS: A Retrospective ," Artificial Intelligence , vol. 59, pp. 227-232, 1993.

Nilsson, N., " Teleo-Reactive Programs for Agent Control ," Journal of Artificial Intelligence Research , 1:139-158, January1994. (All JAIR articles are available in PDF and PostScript from the Journal of Artificial Intelligence Research web site.)

Nilsson, N., " Teleo-Reactive Programs and the Triple-Tower Architecture ," Electronic Transactions on Artificial Intelligence , Vol. 5 (2001), Section B, pp. 99-110. PostScript version available at: http://www.ep.liu.se/ej/etai/2001/006/ .

Conference Proceedings (Invited Papers)

Nilsson, N., " Survey of Pattern Recognition ," Annals of New York Academy of Sciences 161:2, September 1969.

Nilsson, N., " Artificial Intelligence ," Information Processing 74 , pp. 778-801, Amsterdam: North Holland Publishing Co., 1974.

Nilsson, N., "Some Examples of AI Mechanisms for Goal Seeking, Planning and Reasoning, XXI International Congress of Psychology , Paris, France, July 1976.

Refereed Conference Proceedings

Nilsson, N., "An Application of the Theory of Games to Radar Reception Problems," IRE National Conference Record , 1959.

Dausin, L., Niebuhr, K., and Nilsson, N., " The Effects of Wideband Signals on Radar Antenna Design ," IRE WESCON Conference Record, 3, Part 1 , pp. 40-48, 1959.

Munson, J., Brain, A., Forsen, G., Hall, D., Nilsson, N., and Rosen, C., "A Pattern-recognition Facility with a Computer-controlled Learning Machine," Proceedings IFIP Congress , 2:360-361, May 1965.

Rosen, C., and Nilsson, N., "An Intelligent Automaton," Proceedings IEEE International Conference , New York, 1967.

Nilsson, N., "A Mobile Automaton: An Application of Artificial Intelligence Techniques," Proceedings International Joint Conference on Artificial Intelligence , Washington, D.C., May 1969. Available as an SRI AI Center Informal Paper , January 1969.

Nilsson, N., "Searching Problem-Solving and Game-Playing Trees for Minimal-Cost Solutions," in Morrell, A. (ed.), Information Processing 68 , vol. 2, pp. 1556-1562, Amsterdam: North-Holland, 1969.

Duda, R. O., Hart, P. E., and Nilsson, N., "Subjective Bayesian Methods for Rule-Based Inference Systems," Proc. AFIPS Nat. Computer Conference , vol. 47:1075-1082, 1976. Available as SRI AI Center Technical Note , January 1976.

Konolige, K., and Nilsson, N., " Multiple Agent Planning Systems ," Proceedings AAAI National Conference , Stanford University, August 1980.

Essays (some published, some not)

Nilsson, N., " Understanding Research ," text of remarks made at a panel on "Speech Understanding and AI; AI and Speech Understanding," 5th International Joint Conference on Artificial Intelligence-1977, IJCAI-77 Proceedings of the Conference , pp. 973-974, vol. two, 1977.

Nilsson, N., " Artificial Intelligence: Engineering, Science, or Slogan? " The AI Magazine , 3(1), Winter, 1981-82.

Nilsson, N., " Artificial Intelligence Prepares for 2001 ," The AI Magazine , 4(4), Winter 1983.

Nilsson, N., " Introduction to the COMTEX Microfiche Edition of the SRI Artificial Intelligence Center Technical Notes: A Brief History of the SRI Artificial Intelligence Center ," The AI Magazine , 5(1), Spring 1984.

Nilsson, N., " Artificial Intelligence, Employment, and Income ," The AI Magazine , 5(2), Summer 1984.

Nilsson, N., " A Short Rebuttal to Searle ," (unpublished note), November 6, 1984.

Nilsson, N. " Fantasy, Computation, and Reality ," December 14, 1985. (Unpublished version of the 1985 Jacob Bronowski Memorial Lecture given at New College, University of Toronto on November 6, 1985.)

Nilsson, N., " The Mind ," pp. 62-63, The Stanford Magazine , Winter, 1986. [Part of a feature called "What is the Question?"]

Nilsson, N., " Thoughts on Becoming the First Kumagai Professor of Engineering ," (unpublished note), March 18, 1991.

Nilsson, N., " Eye on the Prize ," AI Magazine , 16(2), pp. 9-16, Summer, 1995.

Nilsson, N., " Challenge Problems for Artificial Intelligence: Toward Flexible and Robust Robots ," Proceedings of AAAI-96, Thirteenth National Conference on Artificial Intelligence , pp. 1340-1345, Portland, Oregon, August 1996, AAAI Press, Menlo Park, California, 1996.

Nilsson, N., " Robotics and Artificial Intelligence ," J. Expt. Theor. Artif. Intell. , 9(2-3), pp. 337-338 (preface), April 1, 1997.

Nilsson, N., " Considerations Regarding Human-Level Artificial Intelligence ," (unpublished note), January 2002.

Nilsson, N., " Reconsiderations ," The AI Magazine , 26(4), pp. 36-38, Winter, 2005.

Nilsson, N., " Human-Level Artificial Intelligence? Be Serious! ", The AI Magazine , 26(4), pp. 68-75, Winter, 2005.

Nilsson, N., "Commentary on David Sahner’s 'Human Consciousness and Selfhood',"   Journal of Consciousness Exploration & Research , Vol. 2, Issue 2 | pp. 214-215, March 2011.

Kuipers, B., Feigenbaum, E., Hart, P., Nilsson, N., " Shakey: From Conception to History ," AI Magazine , 38(1), pp. 88-103, Spring, 2017

Other Writings

Brain, A., Forsen, G., Nilsson, N., and Rosen, C., "Learning Machines," International Science and Technology , pp. 20-30, November 1962.

Nils J. Nilsson, Sandra B. Cook, Alan C. Kay, Faye Duchin, Margaret A. Boden, and Dennis Chamot, "Artificial Intelligence: Its Impact on Human Occupations and Distribution of Income," (Panel Discussion),pages 1195-1198 , Proceedings International Joint Conference on Artificial Intelligence, 1983.

Nilsson, N., (ed.), Shakey the Robot , Technical Note 323 , (about 6 MB), SRI International, Menlo Park, CA, 1984. [The SRI film, Shakey The Robot , (563 MB) is also available.]

Nilsson, N. J., " In Memoriam: John G. Gaschnig, June 24, 1950 - March 4, 1982, "  AI Magazine ,  Volume 3,  Number 2, p. 3,  1982.

Nilsson, N., Triangle Tables: A Proposal for a Robot Programming Language , Technical Note 347, SRI International, Menlo Park, CA, February, 1985.

Nilsson, N., " Triangle-Table Trees ," (unpublished note), August, 1990.

Nilsson, N., "Action Networks," Proceedings from the Rochester Planning Workshop: From Formal Systems to Practical Systems , J. Tenenberg, et al. (eds.), University of Rochester, Computer Science Technical Report 284, April 1989.

Nilsson, N., Toward Agent Programs with Circuit Semantics , Technical Report STAN-CS-92-1412, Stanford University Computer Science Department, 1992. (1.1 MB.)

Benson, S., and Nilsson, N., " Reactive Architecture Memo ," (unpublished note), February, 1994.

Nilsson, N. J., " Learning Strategies for Mid-Level Robot Control: Some Preliminary Considerations and Results ," (unpublished note), May, 2000.

Nilsson, N. J., " Predicate-Squish (P-Squish) and Block-Stacking: Rough Preliminary Notes ," April 3, 2002.

Nilsson, N. J., " Questions and Answers ," in R. Dechter, H. Geffner, and J.Y. Halpern, eds., Heuristics, Probability and Causality:  A Tribute to Judea Pearl , pp. 547-551, College Publication, 2010.

Nilsson, N. J., " John McCarthy, 1927-2011: A Biographical Memoir ," National Academy of Sciences, 2012.

Nilsson, N. J., " The Future of Work: Automation's Effect on Jobs--This Time Is Different ," Pacific Standard , October 19, 2015.

Books | Contributions to Books | Archival Journal Articles | Conference Proceedings | Refereed Conference Proceedings | Essays | Other Writings | Movie   | Home page

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Principles of Artificial Intelligence

• © 1982
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• Nils J. Nilsson

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Part of the book series: Symbolic Computation (SYMBOLIC)

Part of the book sub series: Artificial Intelligence (1064)

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Bibliographic Information

Book Title : Principles of Artificial Intelligence

Authors : Nils J. Nilsson

Series Title : Symbolic Computation

Publisher : Springer Berlin, Heidelberg

Copyright Information : Springer-Verlag Berlin Heidelberg 1982

Hardcover ISBN : 978-3-540-11340-9 Published: 01 May 1982

Softcover ISBN : 978-3-662-09440-2 Published: 23 August 2014

Edition Number : 1

Number of Pages : XVI, 476

Additional Information : Jointly published with Tioga Publishing Company

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Problem Solving Methods in Artificial Intelligence

Nilsson, Nils J.

Published by McGraw-Hill, 1971

ISBN 10: 0070465738 / ISBN 13: 9780070465732

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Theory of problem solving;: An approach to artificial intelligence, (Modern analytic and computational methods in science and mathematics)

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Problem-Solving Methods in artificial Intelligence

Nilsson, Nils

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Problem-Solving Methods in Artificial Intelligence

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Artificial intelligence and problem solving methods(Chinese Edition)

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paperback. Condition: New. Paperback. Pub Date: 2017-08-01 Pages: 224 Language: Chinese Publisher: China water conservancy and hydropower press measure an Angle of artificial intelligence is the ability to solve the problem.Artificial intelligence and problem-solving method will we in computer science. mathematics and artificial intelligence course often meet with some of the interesting and challenging problem to a.

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STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving

• R. Fikes , N. Nilsson
• Published in International Joint… 1 September 1971
• Computer Science

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6,091 Citations

Splitting and reduction heuristics in automatic theorem proving, the use of explicit plans to guide inductive proofs, a propositional theorem prover to solve planning and other problems, model checking vs. theorem proving: a manifesto, new methods for proving the impossibility to solve problems through reduction of problem spaces.

• Highly Influenced

Classical AI Planning as Theorem Proving: The Case of a Fragment of Linear Logic

Blackbox : a new approach to the application of theorem proving toproblem, concepts in proof planning, a new logical framework for deductive planning, tabled logic programs, 22 references, application of theorem proving to problem solving.

• Highly Influential

APPLICATION OF THEOREM PROVING TO PROBLEM SOLVING

Toward automatic program synthesis, extracting information from resolution proof trees, review of "problem-solving methods in artificial intelligence by nils j. nilsson", mcgraw-hill pub., prow: a step toward automatic program writing, monitored execution of robot plans producted by strips, robot planning, execution, and monitoring in an uncertain environment, problem-solving methods in artificial intelligence, gps : a case study in generality and problem solving, related papers.

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• 07 August 2024

Physics solves a training problem for artificial neural networks

• Damien Querlioz 0

Damien Querlioz is at Université Paris-Saclay, CNRS, Centre de Nanosciences et de Nanotechnologies, 91120 Palaiseau, France.

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Huge changes are already under way in health care, industry and education as a result of advances in artificial intelligence (AI), but the costs could outweigh the benefits if AI’s enormous energy consumption is not reined in. The problem is that AI relies heavily on deep neural networks, which are layered algorithms that involve millions or even billions of computations, requiring massive, energy-hungry access to the memories in conventional computers. One possible solution is to replace the computers with systems that more closely reflect the physical structure of biological neural networks, but such systems are typically incapable of performing one of the main steps in training the network. In a paper in Nature , Xue et al . 1 report an ingenious workaround that uses physics to overcome the problem.

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Nature 632 , 264-265 (2024)

doi: https://doi.org/10.1038/d41586-024-02392-8

Xue, Z. et al. Nature 632 , 280–286 (2024).

Article   Google Scholar  

McMahon, P. L. Nature Rev. Phys. 5 , 717–734 (2023).

Ross, A. et al. Nature Nanotechnol. 18 , 1273–1280 (2023).

Article   PubMed   Google Scholar  

Ambrogio, S. et al. Nature 620 , 768–775 (2023).

Lee, R. H., Mulder, E. A. B. & Hopkins, J. B. Sci. Robot. 7 , eabq7278 (2022).

Marković, D., Mizrahi, A., Querlioz, D. & Grollier, J. Nature Rev. Phys. 2 , 499–510 (2020).

Wright, L. G. et al. Nature 601 , 549–555 (2022).

Scellier, B., Ernoult, M., Kendall, J. & Kumar, S. Adv. Neural Inf. Proc. Syst . 36 , 52705–52731 (2023); available at https://go.nature.com/4fmijnb .

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Problem-solving methods in artificial intelligence

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Artificial Intelligence Search Methods For Problem solving Week 2

Are you looking for Artificial Intelligence Search Methods For Problem solving Week 2 ? You’ve come to the right place! Access the latest and most accurate solutions for your Week 2 assignment in the Artificial Intelligence Search Methods For Problem solving Week 1 course

Course Link: Click Here

Table of Contents

Artificial intelligence search methods for problem solving week 2 nptel answers, week 2 ga – state space example.

Q1. What information is available in Week 2 notes (bunch of PDFs) published in the course page? About node order and tie breaker How to model a problem as a state space search problem Some properties of state spaces DFS, BFS, DBDFS algorithms and ancillary functions DFID-N, DFID-C algorithms and ancillary functions Examples of list and tuple operations Solved lecture examples Solutions to practice assignment problems Some problems to demonstrate node order

Answer: Updating Soon (In Progress)

Q2. Which of the following states satisfy the capacity constraints of the 12-9-7 water jug puzzle? (3, 2, 7) (3, 4, 5) (1, 9, 2) (0, 4, 8)

For answers or latest updates join our telegram channel: Click here to join

These are Artificial Intelligence Search Methods For Problem solving Week 2 Assignment Nptel Answers

Q3From the state (7, 0, 5), which of the following states can be reached in one or more moves? (3, 2, 7) (3, 4, 5) (1, 9, 2) (0, 4, 8)

Q4. From the state (3,2,7) the least number of moves required to reach (2,3,7) is __________ .

Q5. From the state (2,3,7) the least number of moves required to reach (3,2,7) is __________ .

Q6.Say true or false. In the 12-9-7 water jug puzzle, it is possible to measure all the integral volumes 1L, 2L, …, up to 12L, where each volume measured is present in a single jug. True False Cannot be determined

Q7.The state space shown above __ . is the full state space for the 12-9-7 water-jug puzzle is the subspace reachable from the state (12,0,0) satisfies the “reversible state space” property does not satisfy the “reversible state space” property

Week 2 GA – CLOSED LIST

Q1.Which of the following are possible valid orders in which Depth First Search visits the next 5 nodes starting from K? K E J P O L K J I N P Q K E B A D J K P Q R O S K F L J I N

Q2.Which of the following are possible valid orders in which Breadth First Search visits the next 5 nodes starting from K? K E J P O L K J I N P Q K E L O P J K P Q R O S K F L J I N

Q3. Which of the following are possible valid orders in which Depth First Search visits the next 5 nodes starting from G? G H G L F C G H M L F C G L Q P K L G L Q W X Z G L Q W X W

Q4. Which of the following are possible valid orders in which Breadth First Search visits the next 5 nodes starting from G? G H G L F C G H M F L C G L Q P K L G F L M H Q G F L M H C

Week 2 GA – DFS, BFS and DBDFS

Q1. The BFS search tree is __________ .

Tree 1 Tree 2 Tree 3 Tree 4

Q2. When BFS finds the goal node, i.e., when the GoalTest returns true, the NODEs present in OPEN list are __ .

T he OPEN list contains pairs (NODE,PARENT), ignore the PARENTs and list only the NODEs in the order it occurs in the OPEN list (head to tail).

Q3. List the nodes inspected by BFS. Enter the nodes in the order they were inspected.

These are Artificial Intelligence Search Methods For Problem solving Week 1 Assignment Nptel Answers

Q4. What is the path found by BFS?

Q5. The DFS search tree is __________ .

Q6.When DFS finds the goal node, i.e., when the GoalTest returns true, the NODEs present in OPEN list are __ .

The OPEN list contains pairs (NODE,PARENT), ignore the PARENTs and list only the NODEs in the order it occurs in the OPEN list (head to tail).

Q7. List the nodes inspected by DFS. Enter the nodes in the order they were inspected. a computer program to find proofs a mathematician who works on Logic a program designed by Herbert Simon and Alan Newell a logic based chess player

Q8. What is the path found by DFS?

Q9. When DBDFS (depthBound=2) finds the goal node, i.e., when the GoalTest returns true, the NODEs present in OPEN list are __ .

Q10. List the nodes inspected by DBDFS (depthBound=2). Enter the nodes in the order they were inspected.

Q11. What is the path found by DBDFS (depthBound=2)?

Q12. Which of the following search algorithm(s) always find(s) a path to the goal (if there exists one) in an infinite search space. DFS BFS DFID-C None of the above

Q13 .Mark the algorithm(s) for which space requirements for OPEN grow linearly with depth. DFS BFS DFID-C None of the above

Q14 .Mark the algorithm(s) that always find(s) the shortest path from start state to goal state in any search space. DFS BFS DFID-C None of the above

More Weeks of Artificial Intelligence Search Methods For Problem solving: Click here

More Nptel Courses: https://progiez.com/nptel-assignment-answers