Epstein Secrets

connecting CogPrime to a virtual world (such as Second Life, Multiverse, or Unity3D, to name sonic of the virtual world / gaming platforms to which OpenCog has already been connected in practice). EFTA00624278 132 26 Perceptual and Motor Hierarchies 26.3.1 Perceiving the Virtual World The most comp

can be used for color vision, and multi-sensory and perception-action integration. The approach presented here begins with two separate Al systems, OpenCog (introduced in Chapter 6.3) and DeSTIN (introduced in Chapter 4.3.1) - both currently implemented in open-source software. Here are the relevant fe

somewhat in the de- tails from the manner in which these things would be incorporated into a standalone DeSTIN, but pursuing the same concepts in an OpenCog integration context. What we describe here is a way to make a "Uniform DeSTIN", in which the internal repre- sentation of perceived visual forms is

B is in the AF, both are EFTA00624241 23.6 Dynamics of STI and LTI Propagation 95 It is also worth noting that one can combine ContextLinks with HebbianLinks and express contextual association such that in context C, there is a strong HebbianLink between A and B. 23.5.2 Explicit and Implicit Hebbian Rela

his nature that can be effective in this context We have not yet done any sophisticated experiments in this regard - our current experiments using OpenCog to control robots involve cruder integration of OpenCog with perceptual and motor subsystems, rather than the tight hybridization described in Chapt

obabilistic evolutionary program learn- Mg is an effective method The probabilistic evolutionary program learning method we have worked with most in OpenCog is MOSES, and significant evidence has been gathered showing it to be dramatically more effective than genetic programming on relevant classes of p

ell, is that the cognitive processes must utilize encapsulated maps in a way that gives rise overall to relatively clear clusters in the network of HebbianLinks. This will happen if the encapsulated maps are not too complex for the system's other learning operations to understand. So, there must be useful co

pause to briefly discuss some of the practicalities of work done with the OpenCog system currently implementing parts of the CogPrime architecture. OpenCog, the open-source software framework underlying the "OpenCogPrime" (currently partial) implementation of the CogPrime architecture, has been used for

cessful, this will provide an outstanding platform for ongoing AGI development, as well as a visually appealing and immediately meaningful demo for OpenCog. Specific, particularly simple tasks that are the focus of this project team's current work at time of writing include: • Watch another character

imple example of implicit knowledge in the Atomspace. The "chicken" and "food" concepts are represented by "maps" of ConceptNodes interconnected by HebbianLinks, where the latter tend to form between Con- ceptNodes that are often simultaneously important. The bundle of links between nodes in the chicken map

the present work, it has also been used to control virtual agents in virtual worlds [GEA08]. Prototype work done during 2007-2008 involved using an OpenCog variant called the Open- PetBrain to control virtual dogs in a virtual world (see Figure 6.6 for a screenshot of an OpenPetBrain-controlled virtual d

level of capability will be achievable by simply interposing DeS- TIN (or some other system in its place) as a perception /action “black box” between OpenCog and a robot. Some preliminary experiments in this direction have already been carried out, con- necting the OpenPetBrain to a Nao robot using simpler

simple example of implicit knowledge in the Atomspace. The "chicken" and "food" concepts are represented by "maps" of ConceptNodes interconnected by HebbianLinks, where the latter tend to form between Con- ceptNodes that are often simultaneously important. The bundle of links between nodes in the chicken map a

igence (or any other kind of highly powerful general intelligence), the creation of novel ideas will be paramount. New idea creation takes place in OpenCog via a variety of methods - e.g. inside MOSES which creates new program trees, PLN which creates new logical relationships, ECAN which creates new a

nLinks are created via two basic mechanisms: pattern- mining of associations between importances in the system's history, and PLN inference based on HebbianLinks created via pattern mining (and inference). Thus, saying that PLN inference control relies largely on HebbianLinks is in part saying that PLN infere