Editing Recursive self-improvement (section)

==== Initial architecture ====
The initial architecture includes a goal-following [[Agent-based model|autonomous agent]], that can take actions, continuously learns, adapts, and modifies itself to become more efficient and effective in achieving its goals.

The seed improver may include various components such as:<ref name=":1">{{cite arXiv |last1=Zelikman |first1=Eric |title=Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation |date=2023-10-03 |eprint=2310.02304 |last2=Lorch |first2=Eliana |last3=Mackey |first3=Lester |last4=Kalai |first4=Adam Tauman|class=cs.CL }}</ref>

* '''Recursive self-prompting loop:''' Configuration to enable the LLM to recursively self-prompt itself to achieve a given task or goal, creating an execution loop which forms the basis of an [[Agent-based model|agent]] that can complete a long-term goal or task through iteration.
* '''Basic programming capabilities:''' The seed improver provides the AGI with fundamental abilities to read, write, compile, test, and execute code. This enables the system to modify and improve its own codebase and algorithms.
* '''[[Goal orientation|Goal-oriented design]]''': The AGI is programmed with an initial goal, such as "improve your capabilities". This goal guides the system's actions and development trajectory.
* '''Validation and Testing Protocols:''' An initial [[Test suite|suite of tests]] and validation protocols that ensure the agent does not regress in capabilities or derail itself. The agent would be able to add more tests in order to test new capabilities it might develop for itself. This forms the basis for a kind of [[Evolutionary algorithm|self-directed evolution]], where the agent can perform a kind of [[Selective breeding|artificial selection]], changing its software as well as its hardware.