PhD ideas: Inner class structure

Just typing my ideas down while I work my way through the book.

Within the structure of the agent, I should try and keep it as modular as possible, such that code could easily be reworked without having to rework the entire agent. Of course, this is how I should program anyway, but I should remember this anyway.

This will come in handy when testing multiple policy types and knowledge storage. By having a generic policy interface, the agent could easily swap policy types and make my experiments more streamlined. Also, mostly with regards to policy and the long-term goal, newer policy classes should have methods for reading in the data collected from older policies. So if say, I designed a policy that was good, but not great and rigged it up to a robot which learned a whole lot of information about the world, I would want to transfer the knowledge the bot learned into the newer policy so it doesn’t have to relearn a whole lot of stuff.

On a side note: I freakin’ hate Macs. But I have to use one in the ML lab.

4 Replies to “PhD ideas: Inner class structure”

  1. I haven’t even done any programming yet. I’ve just been using OpenOffice and Safari, and I’m already hating the hell out of Macs.

  2. That’s because you can’t handle the UNIX.

    Eclipse is basically the same across the board.

    Why don’t you install Firefox?

  3. Safari is no problem, nor is Eclipse. It’s the little things, such as how the mouse accelerates on Macs, or how Home and End are used.

    The programs I can handle, it’s the OS itself that annoys me.

    I daresay I hate Macs more than Linux.

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