Silo

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Silo
Author(s)	Xor
Extends	AdvancedRobot

Silo represents the forefront of robocode engineering, being meticulously crafted using cutting-edge reinforcement learning and deep learning methodologies. It is presently in the throes of active development.

Vision

Hand-crafted strategies have their merits, but algorithms that dynamically adapt to evolving distributions are superior. The ultimate objective of Silo is to develop a suite of self-evolving algorithms, capable of outperforming all competitors through continual data updates alone.

Development

The development of Silo unfolds in two interdependent parts, evolving in tandem.

Frameworks

• An advanced robot development framework designed for automated testing and experimentation, which ultimately progresses to self-programming capabilities.
• A comprehensive framework for robot data collection, processing, and model training, tailored specifically for deep reinforcement learning techniques. This integrated system allows for optimization and evaluation of every component within a unified platform.

The frameworks will be made available under a permissive open-source license.

Models

• A cohesive teacher network adept at learning targeting, wave surfing, and energy management in an end-to-end manner.
• Multiple compact networks designed to distill the knowledge acquired and unearthed by the teacher network, ideal for environments with constrained computational resources.