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1 Phase IV – Bayesian Learning Reloaded Operator: Eric Bengfort Temporal Status: End of Week Eight Location: Phase Four Presentation Systems Check: Cleared.

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Presentation on theme: "1 Phase IV – Bayesian Learning Reloaded Operator: Eric Bengfort Temporal Status: End of Week Eight Location: Phase Four Presentation Systems Check: Cleared."— Presentation transcript:

1 1 Phase IV – Bayesian Learning Reloaded Operator: Eric Bengfort Temporal Status: End of Week Eight Location: Phase Four Presentation Systems Check: Cleared Status: Entity… it’s alive!

2 2 Previously… Used Bayesian Learning to probabilistically classify unseen objects based upon their features. Training Data Testing Data Probabilistic Categorization Let’s do something interesting with this ------------------->

3 3 Idea & Goals Use Bayesian Learning to govern how an entity behaves in an environment. Let the classification classes be actions the entity is able to perform. Give the entity minimal instinct to start with, and then set it loose. User is able to praise or scold entity to reinforce proper behavior. Write program generically so that an end user can create any entity with any potential actions inside any environment. Do this in a week.

4 4 Data Driven Everything Everyone loves puppies, lets make a puppy! Puppies have to learn how to behave in real life. Three text files will build our puppy and the world. entity.txt: Name of entity. instinct.txt: Entity’s starting intelligence. Must have at least one example of each possible action/class. worldObjects.txt: Objects entity engages.

5 5 By merely editing text files, unlimited scenarios can be generated and experimented upon. Demonstrates the power of Bayesian Learning in real time. The response from the user (praise/scold) directly influences entity development. My personal testing greatly exceeded personal expectations. Profit Margins

6 6 Launch the demo already!! What I expected. More talk about the internals of the program. The surprising results.


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