TL;DR
This paper explores whether a diagonalizing system can learn to utilize environmental rewards for adaptation, focusing on the role of diagonalization and memory in such learning processes.
Contribution
It investigates the potential for diagonalizing systems to adapt using rewards, introducing new insights into learning mechanisms involving diagonalization and memory.
Findings
Diagonalization-based systems can potentially learn to adapt through rewards.
Memory plays a significant role in the learning process of such systems.
The study provides theoretical insights into the interaction between diagonalization and environmental feedback.
Abstract
We examine the question of whether it is possible for a diagonalizing system, to learn to use environmental reward and punishment as an information, in order to appropriately adapt. More specifically, we study the possiblity of such a system, to learn to use diagonalization on the basis of a rewarding function. Relevant phenomena regarding memory are also investigated.
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