Ensuring Trustworthy and Ethical Behaviour in Intelligent Logical Agents

Reference: Stefania Costantini (2020; arXiv 2024). arXiv:2402.07547v1. Source file: 2402.07547v1.pdf. URL

Summary

Proposes runtime self-checking techniques for computational-logic-based (BDI-style) agents so they can monitor their own behaviour for trustworthiness and ethical compliance, beyond what static a-priori verification can guarantee. The core contribution is A-ILTL (Agent-Oriented Interval Linear Temporal Logic), a specification language for metaconstraints and evolutionary expressions that an agent can apply introspectively to its own state, goals, and actions.

Costantini argues that learning, open MAS, and long-lived autonomous systems make static model checking insufficient; agents must reflect on their behaviour and take counter-measures. The paper relates the approach to self-aware computing, Arkin’s ethical governor, Metacognitive Loops, and “restraining bolts” from reinforcement learning.

Key Ideas

  • Runtime verification (RV) complements static model checking for agents
  • A-ILTL: interval-LTL with metarules for self-checking BDI agents
  • Reification/naming mechanism allows meta-predicates solve/solve_not to gate actions
  • Trace expressions and introspection for ethical reasoning
  • Agents should reflect and self-improve — not merely obey hardcoded rules

Connections

Conceptual Contribution

Tags

#agent-verification #ethics #logic-agents #bdi #runtime-verification

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