|Week 1: Jan 23 - Jan 29||Research and write the Proposal|
|Week 2 - Week 4: Jan 30 - Feb 19||Compare and contrast Total Order Planning and Partial Order Planning in theory. Also develop a Total Order Planning Algorithm. Implement and test it. Deliverable 1|
|Week 5 - Week 7: Feb 20 - Mar 11||Develop a Partial Order Planner. Deliverable 2|
|Week 8 - Week 11: Mar 12 - Apr 07||Convert the above coded Partial Order Planner in an Object Oriented form.Deliverable 3|
|Week 12 - Week 13: Apr 08 - Apr 21||Testing and decision making on GUIs for adding prerequisites into the system.Deliverable 4|
|Week 14 - Week 16: Apr 22 - May 12||Final CS 297 Report. Deliverable 5|
The full project will be done when CS298 is completed. The following will be done by the end of CS297:
Deliverable 1: Implement the Total Order Planning Algorithm and try it on some test cases(situations).
Deliverable 2: Develop a Partial Order Planner.
Deliverable 3: Convert the Partial Order Planner of Deliverable 2 in an Object Oriented form and a few more test cases to it.
Deliverable 4: Sketch web GUIs for adding prerequistes to TO DO events.
Deliverable 5: Final CS 297 Report
 Artificial Intelligence: A Modern Approach. Peter Norvig, Stuart Russell. Prentice Hall Series. 1995.
 Recent Advances in AI Planning. Sussanne Biundo, Maria Fox. ECP, Springer. 1999.
Craig Knoblock, Qiang Yang(1997) Relating the Performance of Partial Order Planning Algorithms to Domain Features . SIGART Bulletin, Vol. 6, No. 1, 8-15
 Intelligent Planning: A Decomposition and Abstraction Based Approach (Artificial Intelligence). Qiang Yang, M Pollack. 1997