Epstein Secrets

g used as the basis for an open-source software project called OpenCog, which is being worked on by software developers around the world. Right now OpenCog embodies only a percentage of the overall CogPrime design as described here. But if OpenCog continues to attract sufficient funding or volunteer in

the ideas presented here are not mere armchair speculation - they are currently being used as the basis for an open-source software project called OpenCog, which is being worked on by software developers around the world. Right now OpenCog embodies only a percentage of the overall CogPrime design as d

validated or refuted via practice. (As a related note: here and there in this book, we will refer to the "current" CogPrime implementation (in the OpenCog framework); in all cases this refers to OpenCog as of late 2013.) To state one believes one knows a workable path to creating a human-level (and po

rithms carrying out separate functions, encapsulated in black boxes and communicating results with each other." For instance, PolyScheme, ACT-R and CLARION all display this "modularity" property to a significant extent. These architectures lack the rich, real-time interaction between the intents/ dynam

w several hybrid architectures in more detail, focusing most deeply on LIDA and MicroPsi which have been directly inspirational for CogPrime. 4.5.1 CLARION Ron Sun's CLARION architecture (see Figure 4.9) is interesting in its combination of symbolic and neural aspects - a combination that is used in a

ing used as the basis for an open-source software project called OpenCog, which is being worked on by software developers around the world. Right now OpenCog embodies only a percentage of the overall CogPrime design as described here. But if OpenCog continues to attract sufficient funding or volunteer inte

at the ideas presented here are not mere armchair speculation — they are currently being used as the basis for an open-source software project called OpenCog, which is being worked on by software developers around the world. Right now OpenCog embodies only a percentage of the overall CogPrime design as des

be validated or refuted via practice. (As a related note: here and there in this book, we will refer to the "current" CogPrime implementation (in the OpenCog framework); in all cases this refers to OpenCog as of late 2013.) To state one believes one knows a workable path to creating a human-level (and pot

intelligence will involve a combination of symbolic and non-symbolic processing.” A few of the more important hybrid cognitive architectures are: ¢ CLARION [SZ04] is a hybrid architecture that combines a symbolic component for reason- ing on “explicit knowledge” with a connectionist component for managin

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

chematics and production rules or other similar constructs, is that in CogPrime this level of knowledge representation is not the only important one. CLARION [SZ04], as reviewed above, is an example of a cognitive architecture that uses production rules for explicit knowledge representation and then uses 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

is one that may be of value for AGI generally beyond the CogPrime design, and is somewhat related to (though different in detail from) the way the CLARION cognitive architecture ISZO-il maps declarative knowledge into knowledge appropriate for its neural net layer. There is an obvious way to project C