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Chapters/3-SOLVING-PROBLEMS-BY-SEARCHING.md
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Chapters/3-SOLVING-PROBLEMS-BY-SEARCHING.md
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# Solving Problems by Searching
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Whenever we need to solve a problem, our `agent` will need to be able to foresee
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outcomes in order to find a `sequence` of `actions` to get to the `goal`.
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Here our `environment` will always be:
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- Episodic
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- Single-Agent
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- Fully Observable
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- Deterministic
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- Static
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- Discrete
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- Known
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And our `agents` may be:
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- Informed: when they know how far they are from the objective
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- Uninformed: when they don't know how far they are from the objective
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## Problem-Solving agent
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This is an `agent` which has `atomic` representations of states.
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### Problem-Solving Phases
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1. Formulate `Goal`
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2. Formulate problem with adequate *abstaction*
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3. Search a solution ***before*** taking any action
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4. Excute plan
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With these 4 phases the `agent` will either come to a `solution` or
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that there are ***none**.
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Once it gets a `solution`, our `agent` will be able to ***blindly execute*** its
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action plan, as it will be ***fixed*** and thus, the `agent` won't need to perceive
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anything else.
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> [!NOTE]
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> This is also called **Open Loop** in Control Theory
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> [!CAUTION]
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> The 3rd and 4th step can be done only in this `environment` as it is `fully-observable`, `deterministic` and `known`,
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> so the `environment` can be predicted at each `step` of the **searching simulation**.
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## Planning Agent
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This is an `agent` which has `factored` or `structures` representation of states.
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## Search Problem
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