Ernest 2.0

As explained by many philosophers and well summurized by (Chaput 2004), to make sense, Ernest's knowledge has to be grounded in his acts. That is, knowldege will take the form of behavioral patterns, which are learned by Ernest during his activity. In psychology, these behavioral patterns are known as Schemas.

We will follow the proposition of Drescher (1991) to implement schemas under the form of triples: (Context, Action, Expectation). Context is a situation where Action can be performed. Expectation is the situation after Action was performed in Context for the first time. Expectation is thus the situation that is expected when the schema is applied again in a similar Context.

Notice that a situation is something sequential. To deal with his new environment, Ernest must manage two sequential situation elements: his previous action (context-a), and the previous environment's answer (context-e).

Ernest learns a new schema after each round. This new schema is added to Ernest's long term memory if it is not already there. So to do, Ernest keeps the current Context and Action in short term memory, until he gets the environment's answer. Both schemas and short term memory are displayed in green in the trace. We can see that Ernest knows more and more schemas as his activity unfolds.

As before, Ernest can do A or B. Here, his environment expects successively A then B. The environment responds Y if this expectation is met, and X if not. Ernest "loves" Y. This love is implemented as an innate preference for Y. That is, if Ernest knows a schema with a context corresponding to the current situation, and with an expectation of Y, he recalls this schema. If not, he acts randomly.

The trace shows that after several rounds, a successful schema has been learnt for any situation. Thus, Ernest becomes able to succeed every time in this "ABAB" environment. Notice that, if placed in the "BBBB" environment that always expects B, Ernest will also learn to succeed every time. Thus, Ernest can now adapt to two different environments, at least.

Reference

Drescher, G. L. (1991). Made-Up Minds, a Constructivist Approach to Artificial Intelligence. Cambridge, MA: MIT Press