Epstein Secrets

. PLN, a probabilistic logic engine; MOSES, an evolutionary program learning algorithm; ECAN, a nonlinear-dynamical attention allocation framework; DeSTIN, a deep learning perception algorithm) within a human-like cognitive architecture. The integration of these multiple learning algorithms is achieved

reinforcement learning mode, to learn small programs that will guide the virtual parrot in achieving its goals (where its goals are managed via the OpenPsi motivational system inside OpenCog, loosely inspired by Joscha Bach's MicroPsi system). • Use of ECAN to learn associational relationships between

. PLN, a probabilistic logic engine; MOSES, an evolutionary program learning algorithm; ECAN, a nonlinear-dynamical attention allocation framework; DeSTIN, a deep learning perception algorithm) within a human-like cognitive architecture. The integration of these multiple learning algorithms is achieved

reinforcement learning mode, to learn small programs that will guide the virtual parrot in achieving its goals (where its goals are managed via the OpenPsi motivational system inside OpenCog, loosely inspired by Joscha Bach's MicroPsi system). • Use of ECAN to learn associational relationships between

nderstanding or generation. A CogPrime approach to speech would be quite feasible to develop, for instance using neural-symbolic hybridization with DeSTIN or a similar perceptual-motor hierarchy. However, this potential aspect of CogPrime has not been pursued in detail yet, and we won't devote space to

chActSchema and SpeechActTriggers) corresponding to fine-grained types of speech act • Dialogue control guided by general cognitive control system (OpenPsi, running within Open Cog) • SpeechActSchema and SpeechActTriggers, in some cases, will internally consult proba- bilistic inference, thus supplying

d tool. However, if one represents low-level procedures like this using another method, e.g. learned cell assemblies in a hierarchical network like DeSTIN, then it's very feasible to make Combo programs that invoke these low-level procedures, and encode higher-level actions like "pick up the cup in fro

cessing. • Defrosting: Restoring, into the RAM portion of an Atomspace, an Atom (or set thereof) previously saved to disk. • Demand: In CogPrime's OpenPsi subsystem, this term is used in a manner inherited from the Psi model of motivated action. A Demand in this context is a quantity whose value the s

c, cognitive and linguistic functions. We will achieve this via the creation and real-time utilization of links between the nodes in CogPrime's and DeSTIN's internal networks (a topic to be explored in more depth Inter in this chapter). 6.4 Memory Types and Associated Cognitive Processes in CogPrime

that recognizes patterns in the hierarchies and passes them to the Atomspace; and imprints patterns from the Atomspace on the hierarchies); and also OpenPsi, a special dynam- ical framework for choosing actions based on motivations. Above the Atomspace we have a host of cognitive processes, which act on

ric, cognitive and linguistic functions. We will achieve this via the creation and real-time utilization of links between the nodes in CogPrime’s and DeSTIN’s internal networks (a topic to be explored in more depth later in this chapter). 6.4 Memory Types and Associated Cognitive Processes in CogPrime N

(that recognizes patterns in the hierarchies and passes them to the Atomspace; and imprints patterns from the Atomspace on the hierarchies); and also OpenPsi, a special dynam- ical framework for choosing actions based on motivations. Above the Atomspace we have a host of cognitive processes, which act on t