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QSeaBattle

A quantum-inspired coordination game framework

What is QSeaBattle?

QSeaBattle is a research and experimentation framework for studying how agents coordinate under severe communication constraints.

Two cooperative players must make a correct decision about a hidden battlefield, but:

  • One player sees everything
  • The other sees almost nothing
  • Only a few classical bits may be communicated

The framework explores when and how (post)quantum-inspired correlations allow agents to outperform purely classical strategies.

Throughout QSeaBattle, coordination beyond direct communication is modeled via shared resources (SR): abstract, pre-established correlations available to both players without signaling. Specific mechanisms—such as classical correlation, quantum entanglement, or Popescu-Rohrlich type correlations—are concrete realizations of shared resources. The framework deliberately avoids treating shared randomness as a primitive; all assisted strategies are expressed uniformly in terms of SR under strict information-flow constraints.

The Core Challenge

At the heart of QSeaBattle is a simple but deep problem:

How much coordination is possible with limited communication?

In each game:

  • Player A observes an \( n \times n \) binary battlefield
  • Player A sends only \( m \ll n^2 \) bits to Player B
  • Player B sees a gun position and must decide whether to shoot
  • Success means guessing the correct value at that position

This setup connects directly to foundational questions in: - Information theory - Quantum correlations - Communication complexity - Multi-agent learning

Why QSeaBattle?

QSeaBattle sits at the intersection of theory, simulation, and learning.

Theory

  • Test information-theoretic limits such as Information Causality
  • Study quantum-like advantages using classical simulations
  • Explore Bell-type correlations and CHSH-style behaviors

Multi-Agent Learning

  • Emergent communication under bandwidth constraints
  • Imitation learning from optimal classical strategies
  • Reinforcement learning with discrete communication
  • Differentiable inter-agent communication (DIAL / DRU)

Neural + Symbolic Methods

  • Combine known algorithms with trainable neural components
  • Inject inductive bias via structured architectures
  • Study when learning can rediscover known quantum-inspired protocols

Architecture Overview

QSeaBattle is organized as a progressive stack, from simple baselines to advanced trainable agents.

  1. Core Game Infrastructure
    Game environment, evaluation, reproducibility, and logging

  2. Deterministic Baselines
    Hand-crafted classical strategies for verification and comparison

  3. Classical Neural Players
    Trainable agents without shared resources

  4. Assisted (Quantum-Inspired) Players
    Classical simulation of quantum correlations using shared randomness

  5. Trainable Assisted Players
    Neural architectures combining learning with quantum-inspired structure

What Makes QSeaBattle Different?

  • Easy to install and use
  • Exact reproducibility
  • Clean separation of theory and learning
  • Designed for experimentation and analysis

QSeaBattle is built to support ablation studies, architecture comparisons, curriculum learning, and theoretical benchmarking.

Getting Started

If you’re new, start here:

  • Quick Start – run your first game
  • Game Mechanics – understand the rules and parameters
  • Deterministic Players – classical baselines
  • Neural Players – learning under constraints
  • Assisted Players – quantum-inspired coordination
  • Training Guides – imitation and reinforcement learning
  • Theory – information-theoretic foundations

Use the navigation on the left to dive in.

Who Is This For?

  • Researchers in quantum information
  • ML practitioners working on multi-agent systems
  • Students exploring communication complexity
  • Anyone curious about the boundary between classical and quantum coordination

Design Philosophy

  • Modular — components are independent and composable
  • Transparent — no hidden state or magic
  • Progressive — complexity increases in layers
  • Research-ready — logging, reproducibility, and analysis built in

Ready to Explore?

Start with the one of the tutorials:

QSeaBattle is designed to reward curiosity — whether theoretical or practical.