---
title: Lecture on Rational Agents
categories: lecture
---

[Overview]() -> [Rational Agents]() -> lecture

# Briefing

+ What is AI?
    + Act or think?  Humanly or rationally?

## The Agent

![Agent is the perceive-think-act cycle](agent.png)

+ Agent: perceive and act
    - vs machine learning
+ A rational agent is one that chooses the right action.
    - what is right?
    - Hume on is-ought
+ Predefined goal
+ Aristotle's algorithm implemented by Newell & Simon (GPL)
    + means-ends analysis
    + we deliberate on means, not on ends

## PEAS

+ PEAS - Performace Measure, Environment, Actuators, Sensors

## Task Environment

+ Properties of the Environment
    + Fully or partially observable
        - can you sense all *relevant* aspects?
    + Single or multi-agent
        - what is an agent?
        - do actions influence other agent?
	- game theory - can you predict other agent's actions?
    + Deterministic or not
    + Episodic or sequential
        - memory
    + Static or dynamic
        - can it change while you think?
	- round-based games are static
    + Discrete or continuous
        - discrete state space
	- discrete time
    + Known or unknown
        - do you have a complete model of the world?
	- a known world may have unknown or stochastic states


## Paradigms or Program Type

1. simple reflex agent
2. model-based agents
3. goal-based agents
4. utility-based agents
5. learning agents

+ Problem Generator