Rational Behaviour and Omniscience

Rational Behaviour and Omniscience

Rational Agent

• If every entry in the agent function is filled correctly then the agent will always do the right thing. Such agent is called as rational agent. Doing the right thing makes agent most successful. So now we need certain methods to measure the success of rational agent.

• When an agent is working in the environment, it generates a sequence of actions according to the percept it receives. This sequence of actions leads to various states of environment. If this sequences of environment state change is desirable, then we can say that agent has performed well. So if the tasks and environment change automatically the measuring conditions will change and hence there is no fixed measure suitable for all agents.

• As a general rule, it is better to design performance measures according to what one wants in the environment, rather than according to how one thinks the agent should behave.

• The rationality depends upon four things –

        1. The performance measure that defines the criterion of success.

        2. The agent's prior knowledge about the environment.

        3. The actions that the agent can perform.

        4. The agent's percept sequence till current till current date.

Based on above four statements rational agent can be defined as follows -

For each possible percept sequence, a rational agent should select an action that is expected to maximize its performance measure given the evidence provided by the percept sequence and whatever built-in knowledge the agent has. Fig. 2.8.1 depits performance measure metric.

The Good and the Bad Agent

• The concept of rational behaviour leads to two types agents, the good agents and In the bad agent. Most of the time the good and bad behaviour (that is performance) of the agent depends completely on the environment.

• If environment is completely known then we get agent's good behaviour as depicted in Fig. 2.8.2.

• If environment is unknown then agent can act badly as depicted in Fig. 2.8.3.

Omniscience, Learning and Autonomy

• An omniscient agent knows the actual outcome of its actions and can act accordingly, but in reality omniscience is impossible.

• Rationality is not same as perfection. Rationality maximizes expected performance where as perfection maximizes actual performance.

• For increasing performance agent must do same actions in order to modify future percepts.

• This is called as information gathering which is important part of rationality. Also agent should explore (understand) environment to increase performance i.e. for doing more correct actions.

• Learning is another important activity agent should do so as to gather information. Agent may know environment completely (which is practically not possible) in certain cases but if it is not known agent needs learn on its own.

• To the extent that an agent relies on the prior knowledge of its designer rather than on its own percepts, we say that agent lacks autonomy. A rational agent should be autonomous - it should learn what it can do to compensate for partial or incorrect prior knowledge.

Figure depicting rationality and omniscience relationship