Foundation-of-Artificial-Intelligence/Chapters/3-SOLVING-PROBLEMS-BY-SEARCHING.md

Solving Problems by Searching

Whenever we need to solve a problem, our agent will need to be able to foresee outcomes in order to find a sequence of actions to get to the goal.

Here our environment will always be:

• Episodic
• Single-Agent
• Fully Observable
• Deterministic
• Static
• Discrete
• Known

And our agents may be:

• Informed: when they know how far they are from the objective
• Uninformed: when they don't know how far they are from the objective

Problem-Solving agent

This is an agent which has atomic representations of states.

Problem-Solving Phases

1. Formulate Goal
2. Formulate problem with adequate abstaction
3. Search a solution before taking any action
4. Excute plan

With these 4 phases the agent will either come to a solution or that there are *none.

Once it gets a solution, our agent will be able to blindly execute its action plan, as it will be fixed and thus, the agent won't need to perceive anything else.

Note

This is also called Open Loop in Control Theory

Caution

The 3rd and 4th step can be done only in this environment as it is fully-observable, deterministic and known, so the environment can be predicted at each step of the searching simulation.

Planning Agent

This is an agent which has factored or structures representation of states.

Search Problem