Epstein Secrets

ulus • RelEx: A specific software component within OpenCog, which provides one way of dealing with natural language Relationship Extraction • SAT: Boolean SATisfaction, as a mathematical / computational problem • SMEPH: Self-Modifying Evolving Probabilistic Hypergraph • SRAM: Simple Realistic Agents Model • STI:

to learn procedures that will maxi- mize some Goal whose Truth Value is estimated via an expected reward calculation (where "reward" may mean simply the Truth Value of some Atom defined as "reward"). Goal-driven learning is more general than reinforcement learning as thus defined; and the learning that CogPrime does, which

ulus • RelEx: A specific software component within OpenCog, which provides one way of dealing with natural language Relationship Extraction • SAT: Boolean SATisfaction, as a mathematical / computational problem • SMEPH: Self-Modifying Evolving Probabilistic Hypergraph • SRAM: Simple Realistic Agents Model • STI:

to learn procedures that will maxi- mize some Goal whose Truth Value is estimated via an expected reward calculation (where "reward" may mean simply the Truth Value of some Atom defined as "reward"). Goal-driven learning is more general than reinforcement learning as thus defined; and the learning that CogPrime does, which

Calculus RelEx: A specific software component within OpenCog, which provides one way of dealing with natural language Relationship Extraction SAT: Boolean SATisfaction, as a mathematical / computational problem SMEPH: Self-Modifying Evolving Probabilistic Hypergraph SRAM: Simple Realistic Agents Model STI: Short Te

to learn procedures that will maxi- mize some Goal whose Truth Value is estimated via an expected reward calculation (where *reward” may mean simply the Truth Value of some Atom defined as ”reward”). Goal-driven learning is more general than reinforcement learning as thus defined; and the learning that CogPrime does, which is