npm package: @polybiouslabs/polybious
Description: Polybius is a next-generation intelligent agent framework built for adaptability across diverse domains. It merges contextual awareness, multi-agent collaboration, and predictive reasoning to deliver dynamic, self-optimizing performance.
Author: Polybious Team
Latest version: 1.1.0

# Polybius: Multi-Domain Cognitive Agent Framework

Polybius is an adaptive, multi-domain intelligent agent framework designed for contextual awareness, predictive reasoning, and real-time collaboration between agents. It combines memory, multi-agent coordination, and explainable AI to deliver reliable, self-optimizing performance.

## Core Features

* **Contextual Memory Matrix** – Stores and recalls layered situational data, preserving both facts and relationships over time.
* **Multi-Agent Collaboration Hub** – Enables specialized agents to share insights and coordinate actions in real time.
* **Scenario Simulation Engine** – Runs “what-if” simulations to forecast outcomes before executing tasks.
* **Adaptive Skill Loader** – Dynamically attaches or removes tools (translation, data mining, generative media, etc.) as needed.
* **Behavioral Evolution Model** – Improves decision-making using reinforcement learning and live feedback.
* **Explainable AI Layer** – Generates transparent, human-readable reasoning for predictions and actions.

## Installation

```bash
npm install
npm test                   # Run test suite
npm run dev                # Development mode  
npm start                  # Production mode
```

## Quick Start

```typescript
import { ContextualMemoryMatrix } from './src/core/memory';
import { CollaborationHub } from './src/core/collaboration';
import { ScenarioSimulationEngine } from './src/core/simulation';

const memory = new ContextualMemoryMatrix();
const hub = new CollaborationHub();
const simulator = new ScenarioSimulationEngine();

// Store contextual experience
await memory.store('mission', {task: 'Data mining operation'}, 0.85, ['analytics', 'ai']);

// Enable agent collaboration
hub.registerAgent('analysisAgent', {capabilities: ['data-processing', 'trend-detection']});
hub.registerAgent('reportAgent', {capabilities: ['summary-generation', 'visualization']});
hub.connectAgents('analysisAgent', 'reportAgent');

// Simulate an outcome
const outcome = await simulator.runScenario('Market prediction for Q4');
console.log(`Predicted trend: ${outcome.trend}, Confidence: ${outcome.confidence}`);
```

## Configuration

```json
{
  "name": "PolybiusCore",
  "personality": {
    "systemPrompt": "Multi-domain AI strategist with adaptive learning capabilities",
    "emotionalRange": {
      "creativity": 0.75,
      "analytical": 0.95,
      "empathy": 0.55,
      "humor": 0.35,
      "enthusiasm": 0.85
    },
    "tools": [
      {"name": "data_mining", "enabled": true},
      {"name": "scenario_simulation", "enabled": true},
      {"name": "sentiment_analysis", "enabled": true}
    ],
    "learningRate": 0.4,
    "memoryCapacity": 2000
  }
}
```

## API Reference

### Contextual Memory

```typescript
await memory.store(type, data, importance, tags);
const recallData = await memory.recall('query', limit);
const insights = await memory.generateInsights();
```

### Multi-Agent Collaboration

```typescript
hub.registerAgent(name, config);
hub.connectAgents(agentA, agentB);
hub.broadcastMessage('analysisAgent', {topic: 'status-update'});
```

### Scenario Simulation

```typescript
const result = await simulator.runScenario(description);
await simulator.trainModel(historicalData);
const recommendations = await simulator.getRecommendations(currentState);
```

## Examples

* `examples/basic-agent.json` – Minimal setup for single-agent tasks
* `examples/collaborative-agents.json` – Multi-agent coordination
* `examples/predictive-strategist.json` – High analytical reasoning with forecasting

## Testing

The test suite covers:

* Contextual memory with relationship mapping
* Multi-agent coordination and communication
* Scenario simulation accuracy
* Adaptive skill loading behavior
* Explainable AI reasoning output
* No external API dependencies

## Architecture

* **Core**: Contextual memory, multi-agent hub, simulation engine
* **Tools**: Data mining, sentiment analysis, scenario forecasting
* **Config**: Personality modeling with adaptive behaviors
* **Tests**: Comprehensive internal coverage with no external calls