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- Dictionaryrational/ˈraʃən(ə)l/
adjective
- 1. based on or in accordance with reason or logic: "I'm sure there's a perfectly rational explanation" Similar Opposite
- 2. (of a number, quantity, or expression) expressible, or containing quantities which are expressible, as a ratio of whole numbers.
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6. When we use the term rationality in AI, it tends to conform to the game theory / decision theory definition of rational agent. In a solved or tractable game, an agent can have perfect rationality. If the game is intractable, rationality is necessarily bounded. (Here, "game" can be taken to mean any problem.)
Apr 9, 2021 · Later, they define this performance measure in the context of rational agents in section 2.2. If the sequence is desirable, then the agent has performed well. This notion of desirability is captured by a performance measure that evaluates any given sequence of environment states. So, here, a performance measure evaluates a sequence of states.
Dec 12, 2021 · rational agents do the "right" thing (where "right", of course, depends on the context) simple reflex agents select actions only based on the current percept (thus ignoring previous percepts) model-based reflex agents build a model of the world (sometimes called a state ) that is used to deal with cases where the current percept is insufficient to take the most appropriate action
Clearly and also intuitively, rationality is well defined. Intelligence as seen form mathematical and computational approach: Intelligence can be the ability for an agent to make rational or irrational decisions, on a varying time frame and also choose the level of rationality (strictly in a computational sense).
Oct 19, 2021 · The agent correctly perceives its location and whether that location contains dirt. In the book, it is stated that under these circumstances the agent is indeed rational. But I do not understand such percept sequence that consists of multiple [A, clean] percepts, e.g. {[A, clean], [A, clean]}. In my opinion, after first [A, clean], the agent ...
Aug 28, 2016 · In section 2.4 (p. 46) of the book Artificial Intelligence: A modern approach (3rd edition), Russell and Norvig write The job of AI is to design an agent program that implements the agent function...
May 22, 2021 · Now, in their 3rd edition of the AIMA book, Russell and Norvig define fully observable environments as follows. Fully observable vs. partially observable: If an agent's sensors give it access to the complete state of the environment at each point in time, then we say that the task environment is fully observable.
For example, you might have more evidence for more tuples than others, so you may be more uncertain for certain tuples/transitions than others. So, the dataset alone doesn't define the model. You still need to define the probabilities (will you just use the empirical frequencies?) or how to sample. $\endgroup$ –
Dec 24, 2021 · Isn't the belief MDP a stochastic representation of the underlying POMDP (it just requires us to define the belief)? "As a corollary, I would say that this indeed implies that there really is some fundamental difference between the two." But the belief MDP does have a deterministic policy, in which case it actually suggests some equivalence?
Jan 24, 2020 · According to the book "Artificial Intelligence: A Modern Approach", "In a known environment, the outcomes (or outcome probabilities if the environment is stochastic) for all actions are given.", an...
