Building rational agents
What exactly is a
rational agent? Before that, let us define the word rationality.
Rationality: refers to doing the right thing in a given circumstance. This needs to be
performed in such a way that there is maximum benefit to the entity performing
the action.
An agent is said to
act rationally if, given a set of rules, it takes actions to achieve its goals.
It just perceives and acts according to the information that's available. This
system is used a lot in AI to design robots when they are sent to navigate
unknown terrains.
How do we define the right thing? The answer
is that it depends on the objectives of the agent. The agent is supposed to be
intelligent and independent. We want to impart the ability to adapt to new
situations. It should understand its environment and then act accordingly to
achieve an outcome that is in its best interests. The best interests are
dictated by the overall goal it wants to achieve. Let's see how an input gets
converted to action:
How do we define the performance measure for a rational agent? One might say that
it is directly proportional to the degree of success. The agent is set up to
achieve a particular task, so the performance measure depends on what
percentage of that task is complete. But we must think as to what constitutes
rationality in its entirety. If it's just about results, can the agent take any
action to get there?
Making
the right inferences
is definitely a part of being rational, because the agent has to act
rationally to achieve its goals. This will
help it draw conclusions that can be used successively. What about situations
where there are no provably right things to do? There are situations where the
agent doesn't know what to do, but it still has to do something. In this
situation, we cannot include the concept of inference to define rational
behavior.
