Computational-level Analysis of Constraint Compliance for General Intelligence

• URL: http://arxiv.org/abs/2303.04352v3
• Date: Thu, 15 Jun 2023 15:03:11 GMT
• Title: Computational-level Analysis of Constraint Compliance for General Intelligence
• Authors: Robert E. Wray, Steven J. Jones, John E. Laird
• Abstract summary: Rules, manners' laws, and moral imperatives are examples of classes of constraints that govern human behavior. Despite such messiness, humans incorporate constraints in their decisions robustly and rapidly. General, artificially-intelligent agents must also be able to navigate the messiness of systems of real-world constraints.
• Score: 4.383011485317949
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Human behavior is conditioned by codes and norms that constrain action. Rules, ``manners,'' laws, and moral imperatives are examples of classes of constraints that govern human behavior. These systems of constraints are "messy:" individual constraints are often poorly defined, what constraints are relevant in a particular situation may be unknown or ambiguous, constraints interact and conflict with one another, and determining how to act within the bounds of the relevant constraints may be a significant challenge, especially when rapid decisions are needed. Despite such messiness, humans incorporate constraints in their decisions robustly and rapidly. General, artificially-intelligent agents must also be able to navigate the messiness of systems of real-world constraints in order to behave predictability and reliably. In this paper, we characterize sources of complexity in constraint processing for general agents and describe a computational-level analysis for such constraint compliance. We identify key algorithmic requirements based on the computational-level analysis and outline an initial, exploratory implementation of a general approach to constraint compliance.

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