Kristinn R. Thórisson
Kristinn R. Thórisson (Þórisson) is an Icelandic artificial intelligence researcher, founder of the Institute for Intelligent Machines (IIIM) and co-founder and former co-director of the Center for Analysis and Design of Intelligent Agents (CADIA). Thórisson is one of the leading proponents of artificial intelligence systems integration. Thórisson is a proponent of artificial general intelligence (AGI) (also referred to as strong AI) and has proposed a new methodology for achieving artificial general intelligence. A demonstration of this constructivist AI methodology has been given in the FP-7 funded HUMANOBS project HUMANOBS project, where an artificial system autonomously  learned how to do spoken multimodal interviews by observing humans participate in a TV-style interview. The system, called AERA, autonomously expands its capabilities through self-reconfiguration. Thórisson has also worked extensively on systems integration for artificial intelligence systems in the past, contributing architectural principles for infusing dialogue and human-interaction capabilities into the Honda ASIMO robot. Kristinn R. Thórisson is currently managing director for the Icelandic Institute for Intelligent Machines and an associate professor at the School of Computer Science at Reykjavík University. He was co-founder of semantic web startup company Radar Networks, and served as its Chief  Technology Officer 2002–03. Constructivist AI methodology. The constructivist AI methodology proposed by Thórisson addresses the numerous significant challenges involved in building AGI systems, by replacing the top-down architectural design approaches that are ubiquitous today with methods that allow a system to autonomously manage its own cognitive growth. This involves a shift of focus from manual design of mental functions to the principles from which intelligent systems can grow through self-organization. The methodology was inspired in part by Piaget's theory of cognitive development and motivated by the level of operational complexity that will be required for realizing AGI  systems in contrast to what can be achieved with even large teams of human software engineers and software designers relying on methods of manual construction. The constructivist AI approach has been successfully demonstrated in the HUMANOBS project, where a domain-independent AI system autonomously learned real-time socio-communicative behavior through observation. The project was funded by the European Union under an FP-7 STReP grant (number 231453). Constructionist design methodology. The constructionist design methodology (CDM), was developed by K. R. Thórisson and his students at Columbia University and Reykjavik University (c.f. Thórisson et al. 2004, Thórisson & Jonsdottir 2008) for use  in the development of cognitive robotics, communicative humanoids and broad AI systems. The creation of such systems requires integration of a large number of functionalities that must be carefully coordinated to achieve coherent system behavior. Fusing some of the best principles from prior AI methods, including subsumption architecture, modular construction, and behavior-oriented design (BOD), and classical AI, CDM presents iterative design steps that lead to the creation of a network of named interacting modules, communicating via explicitly-typed streams and discrete messages. Publications. A collection of selected publications can be found on K. R. Thórisson's MIT website. In  December 2012 Thórisson and his co-authors received the "Kurzweil Best AGI Idea" prize for their paper "On Attention Mechanisms for AGI Architectures: A Design Proposal" at the Fifth Conference for Artificial General (AGI 2012) in Oxford, UK. In December 2013 Thórisson and his co-authors received the "Kurzweil Best AGI Idea" prize for their paper "Resource-Bounded Machines are Motivated to be Efficient, Effective, & Curious" at the Sixth Conference for Artificial General (AGI 2013) in Beijing, China. In July 2014 Thórisson and his collaborators received the Outstanding ("best") Paper Award for their paper Autonomous Acquisition of Natural Language at  the IADIS International Conference on Intelligent Systems & Agents 2014 (ISA-14).