arXiv AI
Jul 20
Logic, Optimization, and Artificial Intelligence
arXiv:2607. 15532v1 Announce Type: new Abstract: Logic and optimization can, in combination, make valuable contributions to rule-based AI.
A Simple Doxastic Deontic Logic for Norm-Guided Decision Making
The paper presents a doxastic deontic logic designed for autonomous decision‑making under conflicting norms and uncertain information. It extends Chellas' Minimal Deontic Logic with explicit conditional norms and integrates it with multi‑agent KD45 to allow norms to depend on agents’ beliefs about facts and other norms. The authors formulate a Doxastic Norm Compliance Optimization Problem, distinguishing subjective from objective optimization, and identify conditions where the two coincide and where optimal decisions can be computed via weighted partial MaxSAT in polynomial time.
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arXiv AI
Sep 15
Moral Rebel Agents: Decision-Making Under Conflicting Obligations
The paper introduces the concept of moral rebellion in autonomous agents, where agents may deviate from user‑assigned tasks when morally justified. Five agent architectures are formalized: an amoral agent, utilitarian agents, deontic agents, utilitarian‑deontic (UD) agents, and dutiful agents. Experiments in a Mini Search‑and‑Rescue domain show distinct trade‑offs among task completion, rescue outcomes, and norm compliance, highlighting the role of commitment‑aware moral reasoning.
arXiv AI
Aug 6
Approximate Multi-Objective Search Under Rulebooks
arXiv:2608. 04398v1 Announce Type: cross Abstract: Robotic planning often involves multiple objectives with complex priority relationships, such as safety, efficiency, and regulatory compliance.
arXiv AI
Jun 4
DAR: Deontic Reasoning with Agentic Harnesses
arXiv:2606. 05009v1 Announce Type: cross Abstract: Deontic reasoning is the task of answering questions by applying explicit rules and policies to case-specific facts, for example computing tax liability under a statute or determining the outcome of an immigration appeal.
arXiv AI
Jun 2
Defeasible Conditional Obligation in a Two-tiered Preference-based Semantics (Extended Version)
arXiv:2604. 26977v2 Announce Type: replace-cross Abstract: In response to a concern raised by Horty, this paper develops a two-tiered, preference-based semantic framework for modeling defeasible conditional obligations.
arXiv AI
Oct 31
Deogen: Automatic Benchmark Generation for Reasoning over Policies
DeoGen is an automatic, scalable, and parametric benchmark generator for deontic reasoning, which involves applying policy rules to facts to determine verdicts. It autoformalizes policy rules into first‑order logic, builds decision trees whose paths become benchmark entries, and produces combinatorially many entries per tree depth. Evaluations show state‑of‑the‑art models achieve 89‑92% accuracy on verdict‑determining paths but only 22‑40% on paths lacking sufficient information, even when instructed to abstain.
arXiv Machine Learning
Aug 18
The Ethical Decision Head: Operationalizing Normative Ethics in Autonomous Vehicles via Reinforcement Learning from Human Feedback
arXiv:2608. 16710v1 Announce Type: new Abstract: As autonomous vehicles (AVs) approach Level 4 and Level 5 operational capability [SAE International, 2018], their on- board decision systems must handle not only safety-critical locomotion but also their subsequent moral weight.
arXiv AI
Sep 15
Legislating World-Model-Based Planning with Legal Reasoning
arXiv:2609.15113v1 Announce Type: cross Abstract: As robotic systems grow more general, legal norms are needed to integrate them into society. This paper extends the isomorphism problem of aligning l...
arXiv AI
Jul 20
From Black Box to Executable Logic: Explainable Reinforcement Learning through Prolog Expert Systems
arXiv:2607. 15459v1 Announce Type: new Abstract: A trained deep reinforcement learning policy is a black box, and we ask whether it can be made explainable by rewriting it as an executable logic program that reproduces its behaviour and that a person can read, a logic engine can run, and an optimizer can edit.
arXiv AI
Jul 2
Mechanical Conscience: A Mathematical Framework for Dependability of Machine Intelligence
arXiv:2605. 03847v3 Announce Type: replace Abstract: Distributed collaborative intelligence (DCI), encompassing edge-to-edge architectures, federated learning, transfer learning, and swarm systems, creates environments in which emergent risk is structurally unavoidable: locally correct decisions by individual agents compose into globally unacceptable behavioral trajectories under uncertainty.
arXiv AI
Jul 24
Explainable Belief Harmonization under Dynamic Epistemic Partitions
arXiv:2607. 21210v1 Announce Type: cross Abstract: Existing approaches to multi-agent belief combination have established mature foundations for combining uncertain beliefs under common assumptions: consensus methods use iterative averaging, logic-based methods resolve conflicting knowledge bases, and epistemic logic analyzes agents' information states.
arXiv AI
Jun 12
Mechanical Conscience: A Mathematical Framework for Dependability of Machine Intelligenc
arXiv:2605. 03847v2 Announce Type: replace Abstract: Distributed collaborative intelligence (DCI), encompassing edge-to-edge architectures, federated learning, transfer learning, and swarm systems, creates environments in which emergent risk is structurally unavoidable: locally correct decisions by individual agents compose into globally unacceptable behavioral trajectories under uncertainty.