CSCE 580 Presentations

Graduate student will prepare a PowerPoint-based presentation of 35 minutes. You may use of different presentation software, but I must agree in advance. You may also negotiate a change in the duration of your presentation. 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 student presentations:

  • 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.)
  • 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. 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. 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.
  • Some advice on oral presentations from Mark Hill and David Patterson How to give a good presentation, by Kati Compton and Mark Chang