Adaptive Arena-based Contestable Argumentative Network-of-Experts for Open-Ended Care Plan Coordination
Care plan coordination demands synthesizing heterogeneous clinical, functional, and psychosocial information across multiple professional disciplines, where monolithic LLM pipelines cannot perform in a transparent or safe manner. We present CANOE (Contestable Argumentative Network-of-Experts), a multi-agent neuro-symbolic framework that addresses these limitations through five modules: complexity assessment, adaptive team recruitment, role-based argumentative computation via an Arena-based Quant
Record details
Published: 5 August 2026
Source: arXiv
Category: Research
Topics: Healthcare · Agents & autonomy · Transparency
Retrieved: 7 August 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
CARE-Bench: Benchmarking Patient-Facing LLM Triage
arXiv cs.AI · 4 August 2026
SHRIMP: Iterative Refinement of Robot Task Plans
arXiv cs.HC · 9 August 2026
Unmasking Toxic Mimicry in Medical Offline Reinforcement Learning for ICU Sepsis Management via Counterfactual Clinical Audits
arXiv cs.CY · 13 August 2026
Making Agent-Mediated Contributions Governable: A Project-Level Governance Manifest for Open-Source AI Collaboration
arXiv · 17 July 2026
Towards Autonomous and Auditable Medical Imaging Model Development
HuggingFace Daily Papers · 11 July 2026
Always-OnAgents:A Survey of Persistent Memory, State, and Governance in LLMAgents
arXiv · 29 June 2026
How to cite this record
ethics.ai (5 August 2026), “Adaptive Arena-based Contestable Argumentative Network-of-Experts for Open-Ended Care Plan Coordination,” evidence record 17095, https://ethics.ai/record/17095 (originally published by arXiv).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.