CHREST models of implicit learning and board game interpretation

A general theory of intelligence must include learning, the process of converting experiences into retrievable memories. We present two CHREST models to illustrate the effects of learning across two different time scales (minutes and years, respectively). The first is an illustration of implicit learning, checking the validity of strings drawn from an artificial grammar. The second looks at the interpretation of boardgame positions. The same learning and retrieval mechanisms are used in both cases, and we argue that CHREST can be used by an artificial general intelligence to construct and access declarative memory.