Consider the possible attributes of an environment among several modalities (observability, determinism, discreteness, etc.). for each, consider the possible options (e.g., deterministic vs. stochastic, or continuous vs. discrete) and compare them. would one prove harder to design an intelligent agent for than the other? why?

(for example, designing an agent for a partially observable environment is naturally more difficult than for a fully observable environment because we cannot be certain of the state and must use additional overhead to maintain some sort of belief state.)

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21-06-2022
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Consider the possible attributes of an environment among several modalities (observability, determinism, discreteness, etc.). for each, consider the possible options (e.g., deterministic vs. stochastic, or continuous vs. discrete) and compare them. would one prove harder to design an intelligent agent for than the other? why?

(for example, designing an agent for a partially observable environment is naturally more difficult than for a fully observable environment because we cannot be certain of the state and must use additional overhead to maintain some sort of belief state.)

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Martebi Martebi · Answer 1 · 2022-06-30T18:34:08+02:00

The option I am going to consider among the above attributes given is deterministic vs. stochastic and I think deterministic model would prove harder to design an intelligent agent.

What are the Comparison between Stochastic and Deterministic Models?

A deterministic system is known to be non-stochastic in nature. It is one that is said to be static and is not subject to alterations.

While a stochastic system is said to be probabilistic in nature as it is one that can be altered or change using calculable probability.

Note also that deterministic models brings about the same exact results for a given set of inputs but stochastic models are known to often do the opposite as it shows or depict data and predicts outcomes that brings about some levels of randomness.

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