Epstein Secrets

ogPrime's action selection aspect is fairly similar to MicroPsi (due to the common foundation in Dorner's Psi model), the dynamics are less similar. MicroPsi's dynamics are a little closer to being a formal neural net model, whereas ECAN's economic foundation tends to push it in different directions. The

s some simple simulated financial mechanisms, building on the economic metaphor of ELAN, that are different from, and more complex than, anything in MicroPsi. The main actors (apart from the usual ones like the AtomTable, economic attention alloca- tion, etc.) in the tale to be told here are as follows:

ht of the link from Atom A to Atom B is based on the probability of shared utility of A and B - economic attention allocation consists of spreading ShortTermlmportance and LongTer- mImportance "artificial currency" values (both grounded in the universal underlying "juju" currency value defined further below) betwee

ion and intelligence. It has been tested on some practical control applications, and also on simulating artificial agents in a simple virtual world. MicroPsi's comprehen- siveness and basis in neuroscience and psychology are impressive, but in the current version of MicroPsi, learning and reasoning are ca

nts in a simple virtual world. MicroPsi's comprehen- siveness and basis in neuroscience and psychology are impressive, but in the current version of MicroPsi, learning and reasoning are carried out by algorithms that seem unlikely to scale. OCP incorporates the Psi model for motivation and emotion, so tha

ines represent nodes and links in OpenCogPrimes mem- ory, and stars denote those nodes with a high level of attention (represented in OpenCog by the ShortTermlmportance node variable) at the particular point in time. In this perspective, self, free will and reflective consciousness are specific phenomena occur- ring

ut on the big- picture level the main difference lies in the way the cognitive synergy principle is pursued in the two different approaches. Psi and MicroPsi rely on very simple learning algorithms that are closely tied to the "quad" neurosymbolic knowledge representation, and hence interoperate in a fai

ic truth values of the implications in CogPrime's Context A Procedure -> Good triples. However, in CogPrime this probability is not the same as the ShortTermlmportance "attention value" associated with the Implication link representing that implication. Here LIDA merges together two concepts that in CogPrime are se