Group Learning By Philip Sterne Supervisor : Shaun Bangay Neural Networks: sharing information.

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Presentation transcript:

Group Learning By Philip Sterne Supervisor : Shaun Bangay Neural Networks: sharing information

Group Learning Create virtual Creatures™. Give them the ability to learn through Neural Networks. Place them in Stressful environments. Group Learning vs. Individual Learning

Artificial Life: Moves around and explores its environment. Communicates with other creatures. Has needs, eg – Hunger, thirst Dies if those needs are not met.

Neural Networks Attempt to model the brain. Just like the brain: – Need to be trained. – Can learn new things. – Can forget old things. Perform parallel computations.

Neural Networks Jargon: Inputs (perceptions) Perceptrons Neurons Pathways Outputs

Stressful Environments Predators – Detection. – Evasion. – Warn others. (?) – Remove slow learners. Scarce Food – Forces exploration. – Encourages Cooperation (?)

Group vs. Individual Learning Heart of my Project. In real life: – People learn from other people. – “Birds of a feather flock together” In Neural nets: – “Bad” nets are replaced with “Good” nets, but only after death. – No real interaction.

Group Learning Enable communication. – Pass knowledge (weightings) – Speak to each other. Ensure diversity. – Only “like-minded” nets sharing weightings.

At Present: Neural networks simulate individual learning. No research (yet) on cooperative learning. Focused on – more accurate simulation of the brain. E.g. – Biochemical. – Genetic encoding.

Comparisons: Speed of Learning. Population Dynamics. Cooperation. Communication. End result.

Conclusion: Create Neural Networks. Simulate social learning Will Language develop? Will there be cooperation? Will social learning be faster than in a group of individuals?