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---
title: Lecture on Rational Agents
categories: lecture
---
[Overview]() -> [Rational Agents]() -> lecture
# Briefing
+ What is AI?
+ Act or think? Humanly or rationally?
+ Aristotle's algorithm implemented by Newell & Simon (GPL)
+ means-ends analysis
## Rational Agents
## The Agent
+ Rational Agents
- Hume on is-ought

+ Agent: perceive and act
- vs machine learning
+ Paradigms
1. Simple reflex
2. Model
3. Goal
4. Utility
5. 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