Artificial General Intelligence

2009

Dr. Nil Geisweiller & Dr. Ben Goertzel – Probabilistic Logical Networks (2 parts)


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Dr. Nil Geisweiller – Imitation and Reinforcement Learning in Virtually Embodied Agents Using Program Evolution


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Dr. Joel Pitt – Attractor Neural Nets and Economic Attention Allocation

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Dr. Ben Goertzel – Natural Language Generation: the NLGen Framework

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Dr. Ben Goertzel – Natural Language Processing for AGI: the RelEx Framework

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Dr. Joscha Bach – The MicroPsi Architecture

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HyunRyong Jung – RIDE: A Simulator for Robotic Intelligence Development

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Dr. Joscha Bach – Understanding Motivation, Emotion and Mental Representation

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Dr. Ben Goertzel – Extending and Customizing Virtual Worlds for AGI

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Dr. Hugo de Garis – Humanoid Robotics for AGI: the Nao Platform

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Dr. Joscha Bach – Understanding Motivation, Emotion and Mental Representation

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Dr. Nil Geisweiller – Controlling Intelligent Agents in a Virtual World


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Dr. Joel Pitt with Dr. Ben Goertzel – OpenCog Software Framework



OpenCog aims to provide research scientists and software developers with a common platform to build and share artificial intelligence programs. The long-term goal of OpenCog is acceleration of the development of beneficial AGI, a goal which includes developing tools and protocols for AGI safety. This lecture will describe the OpenCog software framework from a theoretical perspective, and also provide hands-on guidance to working with the code.

Readings

* Hart, David and Ben Goertzel (2008). OpenCog: A Software Framework for Integrative AGI, Proceedings of the First Conference on AGI
* OpenCog wiki site, http://opencog.org (obviously students need not read the whole wiki)


Dr. Nil Geisweiller – Automated Program Learning: the MOSES Algorithm


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Dr. Joscha Bach – Man as Machine

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Dr. Ben Goertzel, Dr. Nil Geisweiller – Program Representation for General Intelligence


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Dr. Matthew Ikle – Managing Uncertainty with Indefinite Probabilities

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Dr. Joel Pitt – Probabilistic Logical Networks in OpenCog


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Dr. Hugo de Garis – Evolvable Neural Networks

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Dr. Allan Combs – Vision and the Brain

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Dr. Allan Combs – Nonlinear Dynamics and the Mind

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Dr. Pei Wang – A Logical Model of Intelligence 3 of 3



NARS (Non-Axiomatic Reasoning System) is designed to serve as the core of general-purpose intelligent systems. It is built according to the belief that “intelligence” is the capability for a system to adapt to its environment while working with insufficient knowledge and resources. This four-day talk will introduce the major components of NARS, and discuss their properties.

Readings

* Toward a Unified Artificial Intelligence, http://nars.wang.googlepages.com/wang.unifiedAI.pdf
* From NARS to a Thinking Machine, http://nars.wang.googlepages.com/wang.roadmap.pdf

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Dr. Joel Pitt with Dr. Ben Goertzel – OpenCog Software Framework 1 of 2

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OpenCog aims to provide research scientists and software developers with a common platform to build and share artificial intelligence programs. The long-term goal of OpenCog is acceleration of the development of beneficial AGI, a goal which includes developing tools and protocols for AGI safety. This lecture will describe the OpenCog software framework from a theoretical perspective, and also provide hands-on guidance to working with the code.

Readings

* Hart, David and Ben Goertzel (2008). OpenCog: A Software Framework for Integrative AGI, Proceedings of the First Conference on AGI
* OpenCog wiki site, http://opencog.org (obviously students need not read the whole wiki)

You can download the entire video here


Dr. Nil Geisweiller & Dr. Ben Goertzel – Introduction to Probabilistic Logic Networks

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The basic principles of the Probabilistic Logic Networks reasoning framework will be presented. The “indefinite probabilities” framework will be briefly reviewed. The basic PLN inference rules will be described, including rules for first order and higher order inference.

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