CIS 5590.004. Artificial General Intelligence

Semantics and Uncertainty

1. Truth and Meaning

Traditional semantics: model-theoretic, conceptual-role, operational

Issues:

Truth: Validity of ampliative inference, Problem of induction
Meaning: Chinese Room argument and Symbol Grounding problem

2. Uncertainty Measurement

Major approaches:

Probability: axiomatic definition and empirical interpretations, Dutch Book argument, Bayesian brain, Cognitive bias
Ignorance: as interval (imprecise probability), higher-order measurement (higher-order probability), or distribution (maximum entropy)
Fuzzy logic: operation and interpretation

3. Experience-Grounded Semantics

Assumption of Insufficient Knowledge and Resources (AIKR):

finite
real-time
open

Experience-Grounded Semantics (EGS):

Evidence
Two-factor truth-value
Multiple representations
Ideal experience and actual experience

A Show of Two Semantics

Reading

Non-Axiomatic Logic: A Model of Intelligent Reasoning, 2nd Edition, Chapter 3