Repository for Term Project Material in 2021
| Time Slot | Title | Presenter |
|---|---|---|
| 9h50 | Operator-Counting Heuristics in HTN Planning | Daniela Kuinchtner |
| 10h05 | Plan Recognition for Behavior Estimation in a Robotic Soccer Player | Douglas Tesch |
| 10h20 | Using Automated Planning in data centers fault tolerance systems | Douglas Trajano |
| 10h35 | Planning Confident Predictions for Semi-Supervised Learning | Eduardo Pooch |
| 10h50 | TBD | Felipe Nunes |
| 11h05 | TBD | Gabriel Henrique |
| 11h20 | TBD | Luciane Boanova |
| 11h35 | TBD | Marlon Silva |
| 11h50 | Planning medical oxygen supply distribution to treat hospitalized COVID-19 patients | Thiago Ferreira |
The first assessment grading criteria is as follows (you should follow the proposed structure).
- Application Domain Complexity (30%) -- How complex the application domain you selected is difficult to model, yet realistically achievable within the course.
- Paper readability (40%) -- How well written the 2-page paper you wrote is, we break this down into the following criteria
- 20% -- Introduction clarity: how well does the introduction answer these questions: what is the problem? Why is it an important problem? How do aim to solve it? And what follows from your proposed solution?
- 10% -- How well do you refer to background material and relate it your proposed application area?
- 10% -- How detailed and realistic you plan the work for the rest of the semester?
- Presentation clarity (30%) -- How well you presented your project proposal, which we break down into three criteria
- 10% -- Use of time during the presentation
- 10% -- Slide quality (conciseness, use of figures, etc)
- 10% -- Presentation organization
The second assessment grading criteria uses two main criteria First, the technical form of the project
- Application Domain Complexity (15%) -- How complex the application domain you selected is difficult to model, yet realistically achievable within the course.
- Domain Modelling (15%) -- How close to the underlying domain is the planning model developed in the project? Are the proposed simplifications justified? What is the trade-off of these simplifications?
- Problem Complexity (15%) -- How complex are the problem instances used in the experimentation? Are these instances computationally challenging or are they just toy problems?
- Formalism Appropriateness (15%) -- Is the selected formalism (Classical Planning of various types, HTN planning, reinforcement learning) appropriate for the selected domain? Is this selection justified?
Second, the report describing the project and its results
- Report Clarity (10%): Is the report clearly written, following the guidelines for part 1
- Report Problem Description (15%): Does the report describe the problem being addressed with enough detail that it can be replicated?
- Report Implementation (15%): Does the report describe the solution both technically and theoretically in a way that allows others to replicate it?
The same criteria for the project presentation applies to the final presentation, with the following weights
- 30% -- Use of time during the presentation
- 30% -- Slide quality (conciseness, use of figures, etc)
- 40% -- Presentation organization