2021-02-dagstuhl-engineering-amee.asciidoc

From Steve Austin �to Peter Norvig : Engineering AMEE, the Simple Autonomous Agent

Table of Contents

• Presentation Outline : Overview
• Steve Austin & Peter Norvig
• Turing’s Imitation Game
• About Agents
• Engineering AMEE
• Summary
• One more thing…​
• Thank you!

Presentation Outline : Overview

• Steve Austin & Peter Norvig

• Turing’s Imitation Game

• About Agents

• Engineering AMEE

• Summary

Steve Austin & Peter Norvig

• Steve Austin

  • "We can rebuild him. We have the technology. We can make him better than he was. Better…​stronger…​faster." — The Six Million Dollar Man, 1973

  • The technology of the day

  • The power of a machine

  • The brain of a human

• Peter Norvig

  • "More data beats clever algorithms, but better data beats more data." — Peter Norvig

  • "How to Write a Spell Corrector" — Peter Norvig (2007) : http://norvig.com/spell-correct.html

  • "Artificial Intelligence : A Modern Approach" — Russell & Norvig (1994)

Turing’s Imitation Game

• Alan Turing

  • "Are there imaginable digital computers which would do well in the imitation game?" — Alan Turing, 1950

About Agents

• Intelligent Agent

  • "Anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators" — Russell & Norvig, "Artificial Intelligence: A Modern Approach" (1994)

• Autonomous Agents

  • "Software entities that carry out operations on behalf of a user with independence and employ knowledge of the user’s goals." — a multiply cited statement in an IBM white paper no longer accessible

• PAGE

  • Percepts, Actions, Goals, Environment

  • Percepts : Something that is perceived.

  • Actions : Something that is done; an act.

  • Goals : A desired result.

  • Environment : Conditions under which you operate.

• Classes of Agents

  • Simple reflex agent : door robot

  • Model-based agent : vacuum robot

  • Goal-based agent : find this vacuum robot for me online

  • Utility agent : buy this vacuum robot at the 'best price'

  • Learning agent : remember where you get the 'best price' on vacuum robots

• Intelligent Autonomous Agents

  • Imitating users

  • Carrying out tasks

  • Using percepts, actions, goals, and environment

  • Via reflex, model, goal, utility, learning

Engineering AMEE

AMEE : The Autonomous Maze Environment Explorer

• AMEE : What is it?

  • AMEE can successfully navigate any 2-dimensional maze of arbitrary size.

  • Agent Class: Goal-based

  • Percepts: Various kinds of doors

  • Actions: Affordances to view, turn, and move

  • Goals: Escape!

  • Environment: XML messages via HTTP protocol

• AMEE : How do we build it? : https://github.com/mamund/2021-02-dagstuhl/blob/master/alps/asd/maze-alps.svg

• AMEE’s algorithm (Model) : https://github.com/mamund/2021-02-dagstuhl/blob/master/images/2021-02-13-maze-bot-model.png

• Coding AMEE (Sensors & Actuators) : https://github.com/mamund/rwa/blob/master/Maze/the-bot/the-bot.js

Summary

• The Future of AMEE

  • AMEE’s Environment : Include rewards (added points) and dangers (lost points)

  • Agent Class : Level up to utility[L4] (scoring) and learning[L5] (improving score)

• Imitating AMEE in the real world

  • Navigation

  • Selection

  • Acquiring

  • Remembering

  • Learning

One more thing…​

• Rene Descartes

  • "It is impossible for a machine to have enough different organs to make it act in all the contingencies of life in the way in which our reason makes us act." — Rene Descartes, Discourse on Method (1637)

• We need lots of AMEEs!

Thank you!

• "We can built it, we have the technology…"

• "Imaginable digital computers…"

• PAGE & Agent Classes

• Engineering AMEE

• "Enough different AMEEs …"