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We can compose steps; but how do you compose score: On page 37, however, the authors state that: This notion of desirability [for a sequence of actions leading to a sequence of states] is captured by a performance measure that evaluates any given sequence of environment states.

I suspect that, whereas the environment is an arbiter of the performance score i. This is corroborated by the following: Notice that we said environment states, not agent states.

Since only the environment has access to its true states, it alone can measure performance. Agent combinators are a little tough, though; the performance measure has to be aware of the combined features. Can we use some kind of message-passing mechanism? What stops us, for instance, as modelling the agents as lambdas; too?

Part of the problem is the inversion of control: Every agent would be a dispatch-mechanism that would manage its own meta-variables including score and e. Is it problematic, however, to have agents managing their own score?

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That way, agents only maintain state according to its percepts. Score, for instance, is not a percept in the vacuum world; location, however, is. Agents, then, are functions with closures; functions which take as many parameters as their percepts have components. How to make the performance measure part of the environment, so that we can relieve the agent from metadata?

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By maintaining agents-as-lambda, we get a certain flexibility; on the other hand, we shunt some complexity onto the environment: Is this an acceptable tradeoff? The alternative, where I need to guess what agents need program, score, location seems onerous; for some reason.

In practice, however, it may be simpler. Can we hash closures? I see now why objects are interesting; closures, of course, do the same thing. Or, we can demand that the user furnish them; better yet, we can give the user the option of furnishing and ignoring them.

This would also have to fall within an external data structure. If we really need to decouple the program from the agent metadata do we? This metadata table, on the other hand, would have to be passed to each subenvironment for composition.

Seems like a pain. For the time being, however, I think using agent-records is simplifying. Message passing simulates records. We could possibly do it with some kind of multiple-return-values hack, in which the subsequent values are ignored the agent effectively does a state dump every time its program is invoked.

The problem with that is that I have to pass a percept in to access its state, or store its state some other way. To avoid namespacing everything like e.Word of the Year.

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