CSCE 580 Presentations

Graduate and honors student will prepare a PowerPoint-based presentation of 35 minutes. Presentations can be made in teams of two. You may use different presentation software, but I must agree in advance. You may also negotiate a change in the duration of your presentation. If you use one of the papers below. You must use at least one reference in addition to the ones mentioned in the description below, and I must agree to the choice of additional reference(s).

Graduate and honors student presentations in spring 2017:

  • 1. Presentation by Xanthidis, Spring 2017. Hadas Kress-Gazit, Georgios F. Fainekos, and George J. Pappas. "Where's Waldo? Sensor-Based Temporal Logic Motion Planning." Proceedings of the 2007 IEEE International Conference on Robotics and Automation, 3116-3121 (local copy).
  • 2. Presentation by Guan and Kanapala, Spring 2017. Ira Pohl. "Heuristic Search Viewed as Path Finding in a Graph." Artificial Intelligence, 1 (1970), 193-204 (local copy). This paper is the foundation for paper (3.).
  • 3. Presentation by Pade, Spring 2017. Natalia Flerova, Radu Marinexu, and Rina Dechter. "Weighted Heuristic Anytime Search: New Schemes for Optimization over Graphical Models." Annals of Mathematics and Artificial Intelligence, 79 (2017), 77-128 (local copy).
  • 4. Presentation by Drobina and Madison, Spring 2017. Jonathan Schaeffer, Neil Burch, Yngvi Bjornsson, Akihiro Kishimoto, Martin Mueller, Robert Lake, Paul Lu, Steve Sutphen. "Checkers Is Solved." Science, 317, 14 September 2007, 1517-1521 (local copy).
  • 5. Presentation by Abeysinghe and Sun, Spring 2017. Joseph K Barker and Richard E Korf. "Limitations of Front-to-End Bidirectional Heuristic Search." Proceedings of the 29th AAAI Conference on Artificial Intelligence (2015), 7 pages (local copy;
  • 6. Presentation by Bates and Ruegamer, Spring 2017. Robert C. Holte, Ariel Felner, Guni Sharon, and Nathan R. Sturtevant. "Bidirectional Search that is Guaranteed to Meet in the Middle." Proceedings of the 30th AAAI Conference on Artificial Intelligence (2016), 7 pages (local copy; local copy of the extended version from Robert Holte's website).
  • 7. Presentation by Khan, Spring 2017. Sandip Aine, Siddharth Swaminathan, Venkatraman Narayanan, Victor Hwang, and Maxim Likhachev. "Multi-Heuristic A*." Int. J. Rob. Res. 35, 1-3 (January 2016), 224-243 (local copy).

    • Graduate and honors student presentations in spring 2015:

  • 1. Kanapala and Balabokhin. Tuesday, March 24, 2015. A* with Non-Additive Costs.
    Section 2.3 ("General Weights, pp.75-80") of: Stefan Edelkamp and Stefan Schroedl. Heuristic Search: Theory and Applications. Morgan-Kaufmann, 2012. (Local copy available on course blackboard site.); and Section 3.3 ("Some Extensions to Nonadditive Evaluation Functions") of: Judea Pearl. Heuristics: Intelligent Search Strategies for Computer Problem Solving. Addison-Welsey, 1984 (local copy).
  • 2. Modassir and Rahman. Thursday, March 26, 2015. Modassir and Rahman. Thursday, March 26, 2015.
    Sections 4.1-4.3 ("Abstraction Transformations," "Valtorta's Theorem," and "Hierarchical A*") of Chapter 4 ("Automatically Created Heuristics," pp.161-192) of: Stefan Edelkamp and Stefan Schroedl. Heuristic Search: Theory and Applications. Morgan-Kaufmann, 2012. (Local copy available on course blackboard site.)
  • 3. Doherty and Zhu. Tuesday, March 31, 2015. The Linear Conflict Heuristic.
    You will present the method of solution criticism for improvement of heuristics derived from relaxed models. The key reference is: Othar Hansson, Andrew Mayer, Moti Yung. "Criticizing Solutions to Relaxed Models Yields Powerful Admissible Heuristics." Information Sciences, 63 (September 15, 1992), 207- 227 (local copy).
  • 4. Wang and Wu. Thursday, April 2, 2015.
    Sections 4.4 ("Pattern Databases") of Chapter 4 ("Automatically Created Heuristics," pp.161-192) of: Stefan Edelkamp and Stefan Schroedl. Heuristic Search: Theory and Applications. Morgan-Kaufmann, 2012. (Local copy available on course blackboard site.)
  • 5. Schober and Zheng. Tuesday, April 14, 2015. Genetic Algorithms.
    Details to be added.
  • 6. Benson and Al Wahah. April 23, 2015. Abductive Diagnosis.
    You will present the basic formalism of abductive diagnosis, one of the the most successful examples of logical knowledge representation and model-based reasoning. The key reference is: David Poole. "Normality and Faults in Logic-Based Diagnosis." Proceedings of the Twelfth International Joint Conference on Artificial Intelligence (IJCAI-91), Sydney, Australia, pp. 1129-1135, August 1991.

    • Some Resources

    Graduate and honors student presentations in fall 2012:

  • 1. Thursday, October 25, 2012. K.L. Denmark, Jason Isenhower, and Ross D. Roessler will present: R.C. Holte, M.B. Perez, R.M. Zimmer, and A.J. Donald. "Hierarchical A*: Searching Abstraction Hierarchies Efficiently." Proceedings of the National Conference on Artificial Intelligence (AAAI-96), pp.530-535 (local copy). You will use the following two papers:
  • 2. Dr. Keith Haynes. Computer Vision Machine Learning Features.
  • 3. Rhea McCaslin. The min-conflict heuristic for CSPs and the million queens problem. Thursday, December 6, 2012.
  • 4. Ahmad Almadhor. Ray Reiter's "A Theory of Diagnosis from First Principles" (http://cs.ru.nl/~peterl/teaching/KeR/Theorist/reiteraij87.pdf), a conceptual introduction. Thursday, December 6, 2012.
  • 5. Hareesh Lingareddy and Srikar Nadipally. Speech Recognition Using the CMU Sphinx Software System. Tuesday, December 4, 2012.

    • Graduate student presentations in fall 2011:

  • 1. Fahim and Simin. Tuesday, November 29, 2011. You will present IDA* as originally proposed in: Richard Korf, "Depth-First Iterative Deepening: An Optimal Admissible Tree Search." Artificial Intelligence, 27 (1985), 97-108. You will present the criticism of IDA* by Russell and some the algorithms that try to improve on it in several ways: Stuart Russell, "Efficient Memory-Bounded Search Methods." In Proceedings of the Tenth European Conference on Artificial Intelligence, Vienna: Wiley, 1992. You will also review one more algorithm from the recent literature.
  • 2. Atluri and Vemulapalli. Tuesday, November 29, 2011. Inconsistent Heuristics and IDA*. Uzi Zahavi, Ariel Felner, Jonathan Schaeffer, and Nathan Sturtevant. "Inconsistent Heuristics." In Association for the Advancement of Artificial Intelligence (AAAI) National Conference, pages 1211-1216, 2007. Ariel Felner, Uzi Zahavi, Robert Holte, Jonathan Schaeffer, and Nathan Sturtevant. "Inconsistent Heuristics in Theory and Practice," Artificial Intelligence, 2011. To appear.
  • 3. Conklin and Lemasters. Tuesday, November 29, 2011. Backtracking Search Vs. Variable Elimination for Propositional Satisfiability
    You will contrast backtracking search vs. variable elimination for propositional satisfiability You will present two algorithms for propositional satisfiability, one due to Davis and Putnam (Davis, M. and Putnam, H. (1960). "A computing procedure for quantification theory." Journal of the ACM, 7(3): 201--215.) and one due to Davis, Logemann, and Loveland (Davis, M., Logemann, G., and Loveland, D. (1962). "A machine program for theorem proving." Communications of the ACM, 5(7): 394--397) and contrast them as done by Rish and Dechter (Irina Rish and Rina Dechter. "Resolution versus Search: Two Strategies for SAT." Journal of Automated Reasoning, 24, 215--259, 2000; local copy).
  • 4. A Prolog-Technology Theorem Prover.
    You will present the sound and complete theorem prover outlined in the following key reference: Donald W. Loveland and Mark E. Stickel. "A Hole in Goal Trees: Some Guidance from Resolution Theory." IEEE Transactions on Computers, vol. C-25, No.4, pp.335-341, April 1976.
  • 5. Benson and Al Wahah (tentative). Abductive Diagnosis.
    You will present the basic formalism of abductive diagnosis, one of the the most successful examples of logical knowledge representation and model-based reasoning. The key reference is: David Poole. "Normality and Faults in Logic-Based Diagnosis." Proceedings of the Twelfth International Joint Conference on Artificial Intelligence (IJCAI-91), Sydney, Australia, pp. 1129-1135, August 1991.
  • 6. Doe and Lam. AI in Video Games.
    Ka Kit Lam and Renaldo Doe. Tuesday, November 29, 2011 (actually presented on 2011-12-06). Evolution of AI in Video Games: This proposal will/may consist of * Video Game algorithms. * The idea behind AI gaming. * Future of AI gaming. * How feasible/knowledgable is AI components in Video Games. * Video Game timeline. * Limitations of AI in Video Games. * How can we improve AI in video games. References: This gives an overview of AI in video games and toys. http://aaai.org/AITopics/VideoGamesAndToys A*, older video games, board game algorithms and methods for video games. http://www.cs.uni.edu/~schafer/courses/previous/161/spring2009/proceedings/papers/paperG.pdf Learning Agents and technologies. http://www.cs.uni.edu/~schafer/courses/previous/161/Fall2010/proceedings/papers/paperG.pdf
  • 7. Parsons and Salvi. Thursday, December 1, 2011. Emotional Representation in A.I.
    I would like to do a presentation on my research topic, which is Emotional Representation in A.I. I will be using the papers, "Genetic Personality and Emotion Simulation in Conversational Agents" by Egges, Kshirsagar, and Magenat-Thalman from MIRAlab at the University of Geneva and "Modeling Emotions and Other Motivations in Synthetic Agents" by Velasquez from the MIT Artificial Intelligence Laboratory, with additional information on Case-Based Reasoning taken from the book "Foundations of Soft Case-Based Reasoning" by Pal and Shiu, and the lecture and Powerpoint presentation on Conversational Case-Based Reasoning by Bhandari.
  • 8. Han and Liu. Thursday, December 1, 2011. Unsupervised learning technique in human motion analysis. Poppe, R. Vision-based human motion analysis: An overview. Computer Vision and Image Understanding, vol.108, No.1--2, pages.4--18, 2007. Applcation of Bayesian networks in human action analysis. The reference is as follows: @inproceedings{park2003recognition, title={Recognition of two-person interactions using a hierarchical Bayesian network}, author={Park, S. and Aggarwal, JK}, booktitle={First ACM SIGMM international workshop on Video surveillance}, pages={65--76}, year={2003}, organization={ACM}}.
  • 9. Guo. Thursday, December 1, 2011. Babak A. Ardekani, PhD and Alvin H. Bachman, PhD. "Model-based Automatic Detection of the Anterior and Posterior Commissures on MRI Scans." Neuroimage. 2009 July 1; 46(3): 677-682.