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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.
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
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
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
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
AGI Education
Phase 1 • Basic Components
Phase 2 • Artificial Toddler
Phase 3 • Artificial Child
Phase 4 • Artificial Adult
Phase 5 • Artificial Scientist
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)
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
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
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