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so that according to the process of synthesis, Y„=W. In practice, of course, the implementation of a
1 Introduction 107 6.2 High-Level Architecture of CogPrime 107 6.3 Current and Prior Applications of OpenCog 108 6.3.1 Transitioning from Virtual Agents to a Physical Robot 110 6.4 Memory Types and Associated Cognitive Processes in CogPrime 110 6.4.1 Cognitive Synergy in PLN 111 6.5 Goal-Ori
bilities, so that we may say: 411011 is the probability distribution of state-sets the organism tends to be in, when its environment is in state-set W. (Recall also that state-sets are fuzzy.) Now one may look at the spaces of world-paths and mind-paths. A world-path is a path through the world's
for building steps available, finding some other way to get elevated will be a good idea that may help it get the object 6.3.1 lb-ansitioning from Virtual Agents to a Physical Robot Preliminary experiments have also been conducted using OpenCog to control a Nao robot as well as a virtual dog HIG081. This inv
so that according to the process of synthesis, Y,=W. In practice, of course, the implementation of a
ime .......... 0.00.00 eee eee eee eee 107 6.3 Current and Prior Applications of OpenCog ..............0..0 022 eee eee 108 6.3.1 Transitioning from Virtual Agents to a Physical Robot ................ 110 6.4 Memory Types and Associated Cognitive Processes in CogPrime ............. 110 6.4.1 Cognitive Synergy i
obabilities, so that we may say: M(W) is the probability distribution of state-sets the organism tends to be in, when its environment is in state-set W. (Recall also that state-sets are fuzzy.) Now one may look at the spaces of world-paths and mind-paths. A world-path is a path through the world’s tr
ls for building steps available, finding some other way to get elevated will be a good idea that may help it get the object 6.3.1 Transitioning from Virtual Agents to a Physical Robot Preliminary experiments have also been conducted using OpenCog to control a Nao robot as well as a virtual dog [GdGO08]. This in
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