Overview
Rock_Paper_Scissors_

Rock Paper Scissors — TriadicFrameworks Module

  • module.json — Agentic module schema role assignments

Path: docs/Rock_Paper_Scissors/
Version: 1.0.0
Updated: 2026-09-09
Domain: Agentic Science · Game-Theoretic Triadics
Status: stable


What This Module Is#

Rock Paper Scissors (RPS) is encoded here not as a game implementation, but as a formal triadic object — a minimal, closed system of three entities whose structure instantiates the full logic of Peircean Firstness, Secondness, and Thirdness, cyclic zero-sum dominance, and multi-tier agentic decision-making.

This module is the canonical entry-level benchmark for the TriadicFrameworks project. It is small enough to be understood completely and rich enough to demonstrate every structural feature of the framework:

  • Three entities, each fully defined as a triadic node
  • A strict cyclic dominance relation with no transitive closure
  • A complete signed payoff matrix
  • A multi-tier agentic protocol grounded in Peircean sign types
  • A formally derived Nash equilibrium with triadic interpretation

Module Map#

Rock_Paper_Scissors/
│
├── README.md               ← You are here
├── index.md                ← Module overview, entity registry, tag index
├── module.json             ← Machine-readable manifest (full schema)
├── module.yaml             ← Lightweight machine-readable manifest
│
├── entities/
│   ├── Rock.md             ← Firstness · Qualisign · crushes Scissors
│   ├── Paper.md            ← Secondness · Sinsign · covers Rock
│   └── Scissors.md         ← Thirdness · Legisign · cuts Paper
│
├── relations/
│   ├── dominance.md        ← Cyclic dominance: formal definition, Z₃ symmetry
│   └── outcomes.md         ← Full 3×3 signed outcome matrix + EV analysis
│
└── agentic/
    ├── agent_protocol.md   ← Tier 0 / 1 / 2 agent decision protocol (Python)
    └── Nash_equilibrium.md ← Formal equilibrium derivation + triadic reading

Core Concept: The Triadic Structure#

Each of the three entities maps to one Peircean phenomenological category:

Entity Position Sign Type Defining Quality
Rock Firstness Qualisign Pure immediacy; brute presence; solidity
Paper Secondness Sinsign Relational coverage; dyadic mediation
Scissors Thirdness Legisign Differentiation; law; habit-cutting

The dominance cycle follows directly from this ordering:

     Rock  (Firstness)
    ↗              ↘
Paper              Scissors
(Secondness)  ←  (Thirdness)

Firstness crushes Thirdness · Thirdness cuts Secondness · Secondness covers Firstness
No mode universally dominates — the cycle encodes the irreducibility of all three categories.


Entity Quick Reference#

Entity Beats Beaten By Draw Nash Weight Novice Freq.
Rock Scissors Paper Rock 1/3 ~35.4%
Paper Rock Scissors Paper 1/3 ~31.7%
Scissors Paper Rock Scissors 1/3 ~32.9%

Outcome Matrix#

Player A's payoff. +1 = win · 0 = draw · −1 = loss.

vs. Rock vs. Paper vs. Scissors
Rock 0 −1 +1
Paper +1 0 −1
Scissors −1 +1 0

The matrix is skew-symmetric (M = −Mᵀ), consistent with zero-sum structure. The unique Nash equilibrium is the *uniform mixed strategy σ = (1/3, 1/3, 1/3)**.


Agentic Protocol Summary#

Three tiers of agent are defined, each corresponding to a Peircean sign mode:

Tier Name Sign Mode Strategy
0 Naive Firstness Uniform random — implements Nash
1 Adaptive Secondness Counters opponent's most frequent observed throw
2 Triadic Thirdness Models opponent's tier; counters their anticipated counter

Full Python implementations and the agentic decision loop are in agentic/agent_protocol.md.


Nash Equilibrium#

The unique Nash equilibrium σ* = (1/3, 1/3, 1/3) is the triadic null state — perfect equipoise across all three Peircean modes. An agent at Nash is maximally unpredictable and therefore maximally robust against exploitation.

Any deviation from σ* is exploitable:

Deviation Optimal Counter Exploiter EV
Rock-heavy (>1/3) Paper always > 0
Paper-heavy (>1/3) Scissors always > 0
Scissors-heavy (>1/3) Rock always > 0

Full derivation in agentic/Nash_equilibrium.md.


How to Use This Module#

As a Framework Reference#

Read index.md for the entity registry, then each entities/*.md file for full triadic definitions. The relations/ files specify the structural backbone; agentic/ files specify how agents operate within the module.

As an Agentic Benchmark#

Import module.json for a machine-readable graph of all entities, relations, and outcome weights. Use the agentic tier protocol as a baseline for evaluating an inference engine's strategic reasoning depth.

As a Teaching Example#

RPS is the minimum viable triadic system: 3 entities, 1 relation type, complete closure. Use it to explain triadic frameworks before introducing more complex modules.


Key Properties of This Module#

Property Value
Entity count 3
Relation type Cyclic dominance (Z₃)
Payoff structure Zero-sum, skew-symmetric
Nash equilibrium Unique mixed strategy (1/3, 1/3, 1/3)
Triadic completeness Full — all three positions occupied
Pure NE None
Evolutionary stability ESS (neutrally stable orbit)
Peirce sign coverage Qualisign · Sinsign · Legisign

Module Relation
Core_Schema Base triadic ontology this module instantiates
Agentic_Protocols General agent decision framework; RPS is a benchmark case

Tags#

triadic · game-theory · zero-sum · cyclic-dominance · Peircean · agentic · benchmark · Firstness · Secondness · Thirdness · Nash · Z3

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