Reykjavik University logo   Intelligence is the foundation of all human activity.
The pursuit of intelligent machines
may be the most important endeavor
humanity can undertake.
  IIIM logo

Some of my older research projects
are hosted on
my M.I.T. pages.

Picture of Kris Thorisson

Kristinn R. Thórisson, Ph.D.

thorissonthe sign that we don't want spambots to interpretru.is


Founding Director of the
Icelandic Institute
for Intelligent Machines

IIIM introductory talk

IIIM introduction on YouTube

IIIM logo

 

Co-founder of Radar Networks, Inc., San Francisco, and inventor of the Twine technology (with Nova Spivack and Jim Wissner), the first large-scale Semantic Web site. Radar Networks was acquired by Evri in 2010.
Paper describing the technology behind the Twine Semantic Web portal:
[PDF
]

 
Humanoid Cognitive Robotics
For the past few years I have been collaborating with the brilliant guys at Honda Research Institute USA and Communicative Machines in developing integrated cognitive architectures for humanoid robots; our Cogntive Map architecture enables Honda ASIMO to play board games with kids.
 
 

Member of IEEE Taskforce onIEEE Taskforce on Huma
Towards Human-like Intelligence



With hard work and a little bit of luck we can make the age-old dream of machines
with human-level intelligence come true in our lifetime.
And as Hans Moravec once pointed out, luck depends on having enough lottery tickets.
The rest is up to research. We've already started
!

HUMANOBS: RoboTV

Have you ever seen a child take apart a favorite toy? Did you then see the little one cry after realizing he could not put all the pieces back together again? Well, here is a secret that never makes the headlines: We have taken apart the universe and have no idea how to put it back together. After spending trillions of research dollars to dissasemble nature in the last century, we are just now acknowledging that we have no clue how to continue - except to take it apart further.

Albert-Lásló Barbasi
Linked - The New Science of Networks
(emphasis: KRTh)


Cognitive Architecture & Sentient Systems

Natural intelligence, as observed in humans and animals, is the result of multiple systems and subsystems, implementing a complex pattern of information flow and control. How can complex interactions between a vast number of largely self-organized functions produce a thinking mind? This question is first and last an architectural one: how the system operates as a whole. Without a deep understanding of architecture we will never understand intuition, attention, insight, creativity, or understanding itself.

My focus is on how the architecture of mind can be implemented in an artificial substrate. By building working – running – models of mind we may be able to kill two flies in one swat: understand the mind and build a practical artificial general intelligence (AGI) systems that can be used for a myriad of tasks, from designing new clothing to cleaning up our attic to helping solve global warming.

Con - struct - ion - ist A.I.: Artificially intelligent manmade system built by hand; learning is restricted to combining predefined situations and tasks, based on detailed specifications provided by a human programmer. While the system may automatically improve performance in some limited domain, the domain itself is decided and defined by the programmer.

Con - struct - iv - ist A.I.: Self-constructive artificial intelligence system with general knowledge acquisition and integration skills. Systems capable of architectural self-modification and self-directed growth; develop from a seed specification; capable of learning to perceive, think and act in a wide range of novel situations and domains and learning to perform a number of different tasks.

The evidence gathered so far on the nature of intelligence makes it highly unlikely that mind appears from a simple – or single – principle. Even a small set of key principles seems unlikely, after all, if it takes a myriad of principles for an automobile engine to run, why should a mind be any different? On the contrary, the mind is the result of a vast amount of interacting components, hooked up in complex ways according to largely unknown principles. This means that if we want to build very smart machines, rivaling the human mind, we need to build more integrated and complete systems than achieved to date. The mind is a system, and my research to date indicates that its operation needs to be captured holistically to achieve truly intelligent machines.

My approach has followed two main traditions in systems thinking. On the one hand is the familiar modular decomposition from cognitive science and software development. Modularization (object-orientation being one expression) is the most accepeted method at present to construct complex systems by hand - constructionist A.I. Unfortunately this method has severe limitations, but until recently there really wasn't a viable alternative available – there is now; keep reading.

As the proponents of the holistic systems approach have pointed out (e.g. Varela, Maturana, Simon) many complex systems have the elusive property that local interactions between their parts are not sufficient to explain, understand or predict the operation of the whole system of which they are part. Software methodologies employing traditional modular decomposition will not be sufficient to allow us to construct such systems in the lab.

If we are ever to see generally intelligent artificial systems we must look towards methodologies that more directly allow us to model and study complex phenomena, calling for an investigation of the principles of self-organization and meta-control. In short, we must employ methods that allow the system to develop on its own, through self-constructive principles. This is constructivist A.I. This topic is the subject of my 2009 AAAI Fall Symposium on Biologically-Inspired Cognitive Architectures keynote speech, as well as the subject of the HUMANOBS Workshop From Constructionist to Constructivist AI held in the fall of 2011, and one of the main topics of our Summer School on Constructivist AI and Artificial General Intelligence.

I have written two papers arguing for why we need constructivist AI and why constructionist AI is not going give us AGI. In the coming months I will be writing and publishing papers on the specifics of constructivist AI and how to apply it to construct real systems that promist to achieve AGI.


Selected Projects

humanobs header image

A.I. research on applying principles of self-organization in the design and implementation of A.I. systems is called constructivist A.I. As it is becoming clear that the manual construction process employed in most of software development wil not be sufficient to construct the kinds of complex architectures that we require for general intelligence, our focus must shift towards using techniques that allow systems to acquire their own knowledge and grow on their own. Without such principles in hand it is unlikely that we will we see systems with architecture-wide integration of learning, attention, analogy making and system growth. Our recently-awarded HUMANOBS project grant from the EU will enable us to take notable steps in this direction.

 

Kris Thórisson
Artificial Gengeral Intelligence conference 2009: Holistic Intelligence: Transversal Skills & Current Methodologies.

Constructivist Papers
Bounded Recursive Self-Improvement
Resource-Bounded Machines are Motivated to be Effective, Efficient & Curious
A New Constructivist AI: From Manual Methods to Self-Constructive Systems
Self-Programming: Operationalizing Autonomy
Achieving Artificial General Intelligence Through Peewee Granularity

 

Eric Nivel
Artificial Gengeral Intelligence conference 2009: Self-Programming: Operationalizing Autonomy

 


Ymir architecture built out in LEGO blocks Ymir architecture built out in LEGO blocks

Constructionist A.I. (not to be confused with constructivist A.I. - see above) is a moniker given to the bulk of A.I. research being performed around the world, where traditional software development methods form the basis of the work.

In this tradition we developed the Constructionist Design Methodology (CDM), which takes the best from the existing such methodologies. CDM has the goal of easing the creation of modular, complex machines that incorporate some aspects of a world-mind interaction loop – perception-action loop. We have used it on the HONDA Asimo humanoid robot and Mirage autonomus virtual agent [Quicktime icon watch movie]. Mirage inhabits an augmented reality; this complex system of integrated heterogeneous components was designed and implemented in as little as 2 mind-months using the CDM. We think it's directly due to the application of CDM in the project [published in A.I. Magazine, winter 2004]. We have also used CDM for a live performance of the Robot Opera in Reykjavik, 2006 [Quicktime icon watch movie] and 2007. One of our main and ongoing projects using the CDM is an artificial radio show host that can conduct a full radio program completely autonomously, including interview listeners over the phone.

Constructionist Papers
Cognitive Map Architecture for Honda ASIMO
Constructionist Design Methdology for Interactive Intelligences
From Constructionist to Constructivist A.I.

 


 
©Kristinn R. Thórisson

 

 
Patents   |   Media
 
S1 agent
RoboTV: Humanoids that Learn to Interact with Humans using Realtime Multimodal Communication by Observing how People do it


Kurzweil Award Plaque - Beijing 2013 . Kurzweil Award plaque - CA 2012
Recently two of my papers were awarded the Kurzweil Prize

H-Plus Magazine logo

H+ MAGAZINE INTERVIEW

Writing an EU FP7 grant prooposal for the first time? You should read my intro to
Research Grant Applications



EQUIVOCAL
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Either Way (2011) features synthpop I authored and recorded at age 17.
The US remake, Prince Avalance, came out in January 2013. Alas, it does not use my music. But it's a good movie.


Co-Founder, AGI Society

AGI Society logo

 


Editorial Board Member


JAGI logo

JAGI cover

Link for submissions



Proceedings Editor
Artificial General Intelligence 2011

AGI Proceedings 2011

Among the top 25% most downloaded eBooks in the Springer eBook Collection 2012
On Amazon



Conference Organizer & Editor
Intelligent Virtual Agents
2011


IVA 2011 Proceedings

 

Editorial Board Member
LNCS Transactions on Computational Collective Intelligence


TCCI Journal

 

 
 

robotspodcast
::Interview on Robotspodcast
March 12 2010 (starts@3:50min)

::AGI talk
March 2009



 
 
 
 
 
 
 

 

 

 

HUMANOBS link