Thesis, Defense, and Source Available

I packaged it all up, documented it, and made it available on-line. Hopefully having a whole LaTeX thesis source on-line will be helpful to someone. This thesis has multiple indices (people and topic), glossaries, and all sorts of PDF hyperlinking and referencing. It uses packages like authorindex, hyperref, index, and natbib. I hope it serves as a good example for putting together a digital book.

• Research Page
  
  • Optimal Foraging Theory Revisited thesis
  • Optimal Foraging Theory Revisited defense presentation
    (best viewed in latest Adobe Acrobat)
• Thesis LaTeX Source Directory


• OhioLink Entry

Archives are also stored in the source directory. The defense presentation is best viewed in latest Adobe Acrobat as it makes use of a number of very modern PDF features. The presentation is built with LaTeX using powerdot.

The source directory also includes a modified osudissert96-mods.sty and the standard osudissert96.cls file, which is part of the osudissert96 (info, source) package. The modifications:

• Force title to uppercase to match updated submission rules.


• Additional hyperref support: If phantomsection defined, will add phantomsection in dedication page.


• Additional hyperref support: alphanumeric page numbers on title page to prevent page name conflicts.

Just so everyone knows, the two acceptable graduate unit names for the OSU ECE department are

• Graduate Program in Electrical & Computer Engineering


• Electrical & Computer Engineering Graduate Program

Finally, a date for the defense!

Finally, after lots of unexpected twists and turns, my MS thesis defense and PhD qualifier has arrived.

The acknowledgments (and abstract and vita) taken from the frontmatter of the document are available on-line. Details of the actual defense are available below. Of course, the public is welcome.

When: Tuesday, June 5, 2007, at 2:30pm

Where: Dreese Labs Room 260

Title: Optimal Foraging Theory Revisited

Abstract: Optimal foraging theory explains adaptation via natural selection through quantitative models. Behaviors that are most likely to be favored by natural selection can be predicted by maximizing functions representing Darwinian fitness. Optimization has natural applications in engineering, and so this approach can also be used to design behaviors of engineered agents. In this thesis, we generalize ideas from optimal foraging theory to allow for its easy application to engineering design. By extending standard models and suggesting new value functions of interest, we enhance the analytical efficacy of optimal foraging theory and suggest possible optimality reasons for previously unexplained behaviors observed in nature. Finally, we develop a procedure for maximizing a class of optimization functions relevant to our general model. As designing strategies to maximize returns in a stochastic environment is effectively an optimal portfolio problem, our methods are influenced by results from modern and post-modern portfolio theory. We suggest that optimal foraging theory could benefit by injecting updated concepts from these economic areas.