July 2009

Xavier Laurent

University of Bangor

Virtual Environments

Meet Artificial Intelligence

Research Focus

Solving how rich virtual worlds need to be

improved to be able to teach an "artificial toddler"

to pass diverse and progressive levels of recognized infantile

cognitive steps.

What is it about?

The Singularity

Ray

Kurzweil

Inventor and

Futurist

Other Views on the Singularity

Dr. Peter

Norvig

Google

Director of

Research

Emulating Intelligence via brain

scanning

Blue brain project(bottom-up or reverse engineering)

An entire neocortical column lights up

with electrical activity. Modeled on a

two-week-old rodent brain, this 0.5 mm

by 2 mm slice is the basic

computational unit of the brain and

contains about 10,000 neurons. This

microcircuit is repeated millions of times

across the rat cortex and many times

more in the brain of a human. Courtesy

of Alain Herzog/EPFL

What is it about?

Artificial General Intelligence and its

Potential Role in the Singularity

Narrow AI

Artificial Intelligence (AI), Artificial General

Intelligence (AGI) or Strong AI or Human

Level Intelligence

Holy Grail of AI: creating machines

that have similar minds to ours.

Unpopularity of AGI

AI winter which promises that could not be kept

Penrose / Hameroff, Intelligence is based on human consciousness which is in turn based on quantum gravity based dynamics operating within brain dynamics (1997, 2002)

Beyond Technology capabilities

Emulating AGI via brain scanning (Kurzweil, 2005)

No immediate results compared to Narrow AI

General purpose systems are not as good as special purpose ones

AGI is dangerous ethical issues

Scaling up of cognitive architectures

Different approaches to AGI

Symbolic

Architecture

• based on logic, good for cognitive function (problem solving, searching or decision making)

Emergent Architecture

• neural network or evolutionary computation, good for processing low level of information (Vision)

Integrative Approach

• combination of the two

Novamente

Definition of Intelligence

It is the ability to achieve complex goal in

complex environment.

Autonomy

Understanding of self and others

Understanding of what is the problem

Ben Goertzel

Novamente Hybrid Approach

Natural language

Loading-in of formally encoded

knowledge

Control of simple

embodied agent

What is it about?

Human Cognitive Development

Sensorimotor Stage

Knowledge that objects exist, independent of

our perception of them

Piaget suggests that until 18 months of age

appearances and disappearance of an object

are not taken as the same object.

Out of sight, out of mind

Circular reaction, object permanence, goal

directed behavior, A not B search error

The Object Permanence

AGI Education

Phase 1 • Basic Components

Phase 2 • Artificial Toddler

Phase 3 • Artificial Child

Phase 4 • Artificial Adult

Phase 5 • Artificial Scientist

What is it about?

Virtual Worlds

Technology Evaluation for Marketing and Entertainment Virtual worlds, July 2008

Virtual Worlds Road Map

What is it about?

Embodiment and AI

Some AI theorists believe that robotic embodiment is necessary for the achievement of powerful AGI (Rodney Brooks for instance is a prominent champion of this perspective)

Others believe embodiment is entirely unnecessary, and one can create a human-level AGI exclusively using other mechanisms, e.g. textual conversation, interaction in formal logic, etc.

Novamente believes that embodiment is extremely convenient for AGI though perhaps not strictly necessary; and that virtual-world embodiment is an important, pragmatic and scalable approach to pursue alongside physical-robot embodiment.

The natural synergy between advanced AI and

gaming/virtual worlds has been avidly discussed

for at least a decade, see (john E.laird 2000)

Why simulated worlds?

Cheaper than robotics

Controllability of the environment with physics

Masses of potential AGI teachers (like Wikipedia or Google implicit knowledge)

Linguistic and embodied perceptual/active experiences (different from chat robots)

Different form of avatars (Virtual animals, shopkeepers etc)

Commercial vehicle for the popularization and monetization of early-stage AGI’s

It's easier for a distributed team to work on project

Virtual Environment Problems

SL does not lend itself well with detailed perceptual and motoric interaction. It is better for its users base. Integration of virtual world platforms with robotics simulation platforms such as Player/Gazebo would be one route.

SL Lack of integrity with other tools

Virtual worlds needs better richness of physics and sensory motions(What must a world be, that an intelligent system may grow and learn within it?)

Object recognition and integration into learning. At present time objects are labeled with metadata indicating their type

Work done in simulated worlds

Object permanence / Object

recognition in AGISIM

False belief test in Second Life

Current SL stage with Novamente

cognition engine, virtual pet (fetch

game)

Novamente AI Sim

Hiding an object and seeing if the AI remembers that it still exists (what Piaget called object permanence)

Fetch games

Using imitation-reinforcement-correctionmethodology to teach avatars various behaviors (verbal and non verbal communication)

Leonardo, the creation of MIT

scientists

Passed the

test of false

Belief

What is OpenCog

The Open Cognition

Framework (OpenCog)

provides research

scientists and software

developers with a

common platform to build

and share artificial

intelligence programs.

http://www.opencog.org/

What do they offer to Kinesthetic learners and how can they be improved in the

future. How virtual worlds can help to develop Intelligence for Human and

Artificial Agents?

Learning style in Virtual Worlds

Road Map

Look at the different type of learning and choose kinesthetic learning style

Fleming and Mills’ Vark model for kinesthetic learners

Virtual worlds vs. other 3D environments, why a Second Life type environment should bring something to kinesthetic learners?

What Virtual Worlds could bring to kinesthetic learners?

What else could be done to improve kinesthetic learning in a virtual world?

Fleming's VARK model

visual learners

auditory learners

reading/writing-preference learners

kinesthetic learners or tactile learners

Kinesthetic learning is when someone learns things from doing or being part of them. They make up about 15% of the population and struggle to pick things up by reading/ listening to things

Naïve Physics

Naive physics (Hayes, 1985) refers to the

theories about the physical world that human

beings implicitly develop and utilize during

their lives.

What goes up must come down.

A dropped object falls straight down.

A vacuum sucks things towards it.

Centrifugal force throws rotating things outwards.

An object is either at rest or moving, in an

absolute sense.

Current Virtual Worlds lack fluids, powders, pastes,

fabrics … they don’t completely implement “naïve

physics”

One likely solution: bead

physics

Spherical beads with

specially designed

adhesion properties can

emulate fluids, fabrics,

pastes, strings, rubber

bands, etc.

Bead physics can be

added to virtual world

physics engines

What Must a World Be That an AGI

Can Develop In It?

Ethical views: Friendly AI

Goal Invariance Under Radical Self-Modification

How to architect an AGI system so as to maximize the odds that, as it radically self-modifies and self-improves, it will not lose track of its originally programmed/taught goal system?

Eliezer Yudkowsky

A Matrioshka brain