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Cognitive Control of Self-Evolving Life Forms (SELF) Utilizing Artificial Procedural Memories

  • James A. Crowder
  • John Carbone
  • Shelli Friess
Chapter

Abstract

As we have discussed at length in the book, the testing of artificial intelligent systems that are designed to learn over time, based on experience and interaction with their environments is, at best, difficult, and in some cases impossible. This is especially true if the methods and mechanisms to capture the adaptation and changing memories are not built into the overall system design. Here we present one notion of testing and control methodologies for self-adapting artificial intelligent entities, using artificial procedural memories. In general, memories involve the acquisition, categorization, classification, and storage of information. The purpose of memory is to provide the ability to recall information and knowledge as well as events. Through our conceptual recollection of the past we can communicate with the world around us and understand events based on past experiences. The purpose here is to describe a new cognitive architecture for artificial intelligence-controlled devices that incorporates artificial procedural memory creation and recall. This cognitive architecture provides a scalable framework for episodic memory creation as an entity experiences events, and, over time, develops procedural memory “scripts” that allow repetition of tasks it has “learned” to accomplish, while effectively managing its internal knowledge economy. These procedural memories will allow the system to “see into” the brain and adaptation of an artificial intelligent entity by keeping track of changes to the procedural memories, recalling them for analysis to understand how they are changing as the artificial intelligent entity interacts with its environment. The system will utilize a temporal-calculus driven spatial map to store spatio-temporal information, as well as the procedural memories. This provides the system with the cognitive abilities to approach task selection and reason via both experiential and spatial learning.

In order to test and evaluate the viability of artificial memory creation and retrieval, a series of artificially intelligent, cybernetic life forms (cyber insects) were created and tested utilizing a combination of analog and digital neural frameworks allowing procedural memory creation, storage, and retrieval as the methodology for autonomous control of the artificial life form. Presented here are initial design and discussion of artificial analog and digital neural structures along with a discussion of the use of artificial procedural memories, used as autonomous cognitive control of the artificial life form. Lastly, future research needs are proposed for improving the continuous balance of knowledge storage and knowledge necessity relative to prime directives and learned objectives in Self-Evolving Life Forms (SELF).

Keywords

Analog neurons Self-evolving life form Artificial intelligence Procedural memory 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • James A. Crowder
    • 1
  • John Carbone
    • 2
  • Shelli Friess
    • 3
  1. 1.Colorado Engineering Inc.Colorado SpringsUSA
  2. 2.ForcepointAustinUSA
  3. 3.Walden UniversityMinneapolisUSA

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