DeepAI AI Chat
Log In Sign Up

Computational-level Analysis of Constraint Compliance for General Intelligence

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.


page 1

page 2

page 3

page 4


Proving Regulatory Compliance: A Computational Complexity Analysis of Elementary Variants

Organisations model their processes using so-called business process mod...

Legible Normativity for AI Alignment: The Value of Silly Rules

It has become commonplace to assert that autonomous agents will have to ...

Teaming up with information agents

Despite the intricacies involved in designing a computer as a teampartne...

Maximum Causal Entropy Inverse Constrained Reinforcement Learning

When deploying artificial agents in real-world environments where they i...

Constraint Reductions

This is a commentary on the CP 2003 paper "Efficient cnf encoding of boo...

Discretizing Dynamics for Maximum Likelihood Constraint Inference

Maximum likelihood constraint inference is a powerful technique for iden...