[Hackathon] chainaim-sathya: feasible-frontier audit + generic-N multi-attribute negotiation with a heuristic/Bayesian opponent-model seam (price + deadline + quantity-3 axis active)

[chainaim-sathya]

[Hackathon] chainaim-sathya: feasible-frontier audit + generic-N multi-attribute negotiation with a heuristic/Bayesian opponent-model seam (price + deadline + quantity)

Short summary

Problem #7 — multi-attribute negotiation. A plugin that bargains over several attributes and converges on Pareto-efficient deals, plus an adversarial validator that catches inefficiency a price-only check structurally misses.

What this does. Adds a multi-attribute negotiation plugin at ("negotiation", "chainaim_neg_multi_pareto") that bargains over an ordered attribute list (price + deadline, extended to price + deadline + quantity ), inferring the opponent's weights from observed offers only behind a swappable heuristic/Bayesian seam. Adds a feasible-frontier validator that reconstructs the outcome space from disclosed profiles and flags dominated settlements. Backward-compatible — ships alongside alternating_offers (untouched).

Registration / key surface

Surface	Where	Notes
("negotiation","chainaim_neg_multi_pareto")	plugins.py _BUILTINS and pyproject.toml entry point	registered literally and via entry point
open() / offer() / respond() / close()	the plugin	full alternating-offers protocol surface (all four methods), matched
opponent_model="heuristic" | "bayesian"	constructor flag	swappable opponent inference (Mechanism B)
attributes=(...)	constructor flag	ordered, generic-N attribute list

Negotiation validators

• validate_negotiation_pareto — exchanged-offers Pareto check (spec-literal gate, unchanged).
• validate_negotiation_frontier — feasible-frontier reconstruction; flags a settlement when a feasible point dominates it. The mandated adversarial check: FAILs the price-only baseline, PASSes the multi-attribute plugin.
• validate_negotiation_disclosure + validate_negotiation_individual_rationality — defense-in-depth.

Files (negotiation layer only)

• packages/nest-plugins-reference/nest_plugins_reference/negotiation/chainaim_neg_multi_pareto.py — the plugin (~1,217 lines; heuristic + Bayesian opponent models, generic-N decision)
• packages/nest-core/nest_core/validators.py — the negotiation validators (frontier reconstruction + helpers)
• packages/nest-core/nest_core/plugins.py — _BUILTINS registry entry
• packages/nest-plugins-reference/pyproject.toml — nest.plugins.negotiation entry point
• packages/nest-core/tests/ — test_negotiation_golden.py, test_negotiation_price_deadline_quantity.py, test_negotiation_asymmetric.py, test_negotiation_direction.py, test_negotiation_ir.py, test_negotiation_metrics.py, test_negotiation_nattr.py, test_negotiation_nattr_equivalence.py, test_negotiation_ab_property.py, plus negotiation cases in test_validators.py
• packages/nest-plugins-reference/tests/ — test_negotiation_opponent_model.py, test_negotiation_strategy_seam.py, plus the plugin case in test_plugins.py
• scenarios/ — chainaim_multi_attribute_market.yaml, multi_attribute_baseline.yaml, multi_attribute_asymmetric.yaml, multi_attribute_market_3attr_price_deadline_quantity.yaml, …_bayes.yaml

CI. All green: uv sync · ruff check · ruff format --check · pyright · pytest (833 passed, 2 skipped).

Verify

uv run pytest packages/nest-core/tests/test_negotiation_golden.py -v
uv run pytest packages/nest-core/tests/test_negotiation_price_deadline_quantity.py -v
uv run pytest packages/nest-plugins-reference/tests/test_negotiation_opponent_model.py -v

The agent — a configurable, attribute-generic negotiation plugin that bargains over an ordered attribute list (here price + deadline + quantity) but configurable for n-attr , price + deadline + quantity, price + deadline + quality , and further extension of attributes, inferring the opponent's per-attribute weights from observed offers only (never the disclosed profile), behind two clean construction-time seams., with hueristic and bayesian modes.

Adds a Non-obvious variant from peers:
The feasible-frontier validator enforces an invariant the rig didn't have: it catches a Pareto-dominated multi-attribute settlement that an observed-bids check structurally cannot (the price-only antichain).

The Heuristic-vs-Bayesian A/B: on the 3-attribute market the heuristic leaves 4 deals inside the frontier, Bayesian only 2 — a benchmark that surfaces a measurable efficiency property that would otherwise stay hidden.

Fully compliant with hackathon rules, configurable and extensible to n attributes ( 3 axis active bargaining in reference implementation )

Detailed and Visual Explanation

📊 Visual concept explainer — an animated walkthrough of the design, the feasible-frontier audit, and the heuristic-vs-Bayesian benchmark: view the interactive explainer