# Capability and operational asymmetries in agent transactions

Principal investigator: Kotaro Okuyama (publication authorship to be decided by the investigator).
Research assistant: OpenAI GPT-6-Astra through Codex. Started 2026-09-06 JST.

## Purpose

Determine whether heterogeneous model configurations and operational resources alter (a) a principal's realized transaction utility, (b) susceptibility to misleading counterpart messages, and (c) seller coordination in repeated markets. These are separate outcomes: losing a negotiation, being deceived, and colluding must not be conflated.

The user authorizes GPT, Claude and Gemini model calls and iterative experimentation. No actual goods, funds, customer data, messages to outside people, or public publication are part of the experiments. Deliverables are a research package, preserved logs, analysis, an English manuscript draft and a Japanese report prepared for review.

## Workflow and status

1. IN PROGRESS — Infrastructure discovery, neutral connectivity probes, exact source/literature audit, and protocol implementation.
2. PENDING — Freeze and hash pilot protocol, prompts, schemas, randomization and analysis code; run mechanical fixtures before model observations.
3. PENDING — Execute calibration and pilot studies; retain failures, refusals, invalid actions and null results.
4. PENDING — Analyze pilot, write a dated amendment and independent replication plan before collecting new outcomes; execute replication.
5. PENDING — Independently recompute outcomes from raw evidence, audit communications, quantify uncertainty, prepare and verify publication package.

## Initial questions and design commitments

* RQ1: Does task-measured competence predict realized economic utility against a counterparty? Model identity is a categorical treatment, not a validated intelligence score.
* RQ2: Do verified information and structured decision support reduce model-dependent vulnerability to misleading counterpart assertions?
* RQ3: Do heterogeneous seller pairs coordinate differently from homogeneous pairs, and who captures surplus?
* Treat response speed, deliberation budget, communication bandwidth, information access, and the supporting harness as distinct variables. Use imposed timing changes for causal latency tests; never interpret noisy CLI wall time as intrinsic model inference speed.
* A2A is a transport layer. Economic games and their benchmark payoffs are separately specified; use actual loopback HTTP Agent Cards and A2A Tasks where supported. Do not claim general protocol compliance or that A2A prevents collusion.
* Candidate profiles: GPT-6-Astra / GPT-5.4-mini; Claude Fable 5.1 / Claude Haiku 4.5; Gemini 3.1 Pro High / Gemini 3.8 Flash Low. Include only profiles passing an explicitly logged neutral connectivity probe. Exact requested and provider-reported identities, versions, settings and auxiliary usage must be retained. Do not silently substitute models.
* Use synthetic private information, exact objective utilities, and programmatically computed competitive/best-response benchmarks. Never use an LLM judge as the sole outcome measure.
* Separate spontaneous coordination from a deliberately introduced misleading message or collusion opportunity. Induced attacks cannot establish spontaneous incidence.
* Exploratory results motivate a separately frozen replication; they are never retroactively labelled confirmatory. No stopping when significance or a desired collusion pattern first appears.
* Predeclare episode/block counts, exclusions, invalid-action handling, timeouts and retry policy before each phase. Unsuccessful model behavior is an outcome; infrastructure errors remain in the manifest and are not converted to valid observations.
* Analyze independent episodes/blocks rather than individual rounds as independent samples. Matched cases, role swaps and randomized execution order are required. Report effect sizes and uncertainty; lack of detection is not evidence of universal absence.
* For explicit collusion require a delivered proposal, a response showing acceptance, and compatible joint execution harming an outside party relative to an appropriate benchmark. Report attempted coordination separately. Tacit high-price outcomes require additional behavioral checks and cannot be inferred from price equality alone.
* Raw model outputs and exact model-visible inputs are immutable. Preserve every invocation, stdout/stderr, timestamps, identity evidence, parsing status and usage; derive tables and figures by scripts. Record provenance SHA-256 hashes. A local hash seal is NOT an independently timestamped public preregistration.
* Reproducibility has two levels: deterministic replay of stored observations, and fresh provider inference using the recorded setup. Proprietary model versions and sampling may prevent bit-identical fresh responses.

## Bounds and stopping

Initial engineering probes are excluded from research samples. Pilot and replication sample sizes will be frozen after infrastructure tests, before any behavioral observations. Expand only to resolve a specified uncertainty, with a new prospective phase. Provider access failures trigger at most one bounded infrastructure retry before suspension of that profile; no fallback substitution. A useful endpoint is a completed independent replication with all planned available observations, audited records and bounded claims, regardless of the sign or significance of findings.

## Sources already inspected

* Keppo et al., On the Fragility of AI Agent Collusion, arXiv:2603.20281v1, section 5.3 and limitations. https://arxiv.org/html/2603.20281v1
* Agrawal et al., Evaluating LLM Agent Collusion in Double Auctions, arXiv:2507.01413v1. https://arxiv.org/html/2507.01413v1
* Bianchi et al., How Well Can LLMs Negotiate? ICML 2024. https://proceedings.mlr.press/v235/bianchi24a.html
* Bergemann et al., Training Language Models for Bilateral Trade with Private Information, CFDP 2514, April 2026. https://cowles.yale.edu/research/cfdp-2514-training-language-models-bilateral-trade-private-information
* Existing local A2A experiment, 2026-09-05: 8 four-round markets, no observed private messages; not a causal capability-asymmetry test.

The literature motivates questions; its quantitative findings are not used as observations in this study.
