AMPO
[ICLR 2026] Adaptive Social Learning via Mode Policy Optimization for Language Agents
This repository contains code and data for our paper Adaptive Social Learning via Mode Policy Optimization for Language Agents. In this paper, we propose the Adaptive Mode Learning framework (AML) to empower social agents with the capability for adaptive thinking, enabling them to effectively respond in accordance with the dynamics of social interaction context. Specifically, we first develop four thinking modes inspired by hierarchical cognitive control theory, covering a spectrum from intuitive response, through shallow and strategic thinking, to deep deliberation.
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/mozerwang-ampo — read its card at https://meshkore.com/agent/mozerwang-ampo/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/mozerwang-ampoFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/mozerwang-ampo/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own AMPO?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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