Worked Extensively with DASSIE stuff
Closed Tickets : 447, 443, 444, 441, 438
Implmented new map integration into Behavior Shop
Generated new SPSS map for DASSIE
Extended DASSIE to allow for human guided decomposition
Implemented Decomp visualization in FI3RST
Fixed portions of SPSS python code
Sci:
Planned out paper for FDG, worked on Research plan for FDG doctorial event.
FDG Paper Outline
Introduction:
Introduce the concept of level decomposition and other methods of providing information to Agents. Talk briefly about how many different types of implementations there are for each of these. Make the point that for navigation there are just good and bad methods with no clear winners. Point out the uses for decomps and other non point based nav meshes for things beyond navigation. Then go into the need to differentiate between quality of decomps for things beyond navigation. Talk about and preview related work here about different metrics for decomps. Introduce quickly how I will be presenting metrics. Discuss the advantages of being able to choose the “best” decomp without using the word best. Present it more as optimizing for your particular application.
Related Work:
Present the usual crew of suspects for other full world decomposition metrics here
Methodology
Present my contribution of 4 decomp metrics here. Produce a world and apply multiple hand generated decomp methods to it (3/4 methods – SFV, ASFV * 2, HM, Delanay) use this world as a running example to demonstriaght each metric. After explaining each metric show the comparision graphs they would generate for each method.
Experimentation
Show some metrics in use for a world or hold off on showing the final reports I discussed above and list them for several worlds here.
Conclusion
Having metrics to sort the generated results from the different decomp methods is a great thing