ITC Agent

ITC Agent is an offline-first AI agent for practical Information Theory and Coding engineering work.

The project is designed for situations where a dedicated information-theory or coding engineer is not available. It is not a study bot. The agent is intended to analyze real engineering problems, build information/source/channel models, select suitable coding methods, implement or simulate solutions, verify results, and produce reproducible technical reports.

Core idea: give the agent an Information Theory & Coding problem and let it execute the engineering workflow from analysis to a verified result.

Objective

Build an AI agent capable of performing useful Information Theory and Coding engineering work autonomously, locally, and with verifiable outputs.

Intended Capabilities

• entropy and information analysis
• joint, conditional, and mutual information
• source modeling and statistics
• source coding and compression analysis
• Huffman coding
• Shannon-Fano coding
• arithmetic and related coding methods
• channel modeling
• channel-capacity analysis
• noisy-channel simulation
• redundancy analysis
• error detection
• error-correcting code analysis
• coding-scheme selection
• encoder and decoder generation
• coding efficiency measurement
• reliability vs redundancy optimization
• algorithm benchmarking
• mathematical verification
• reproducible engineering reports

Agent Workflow

Engineering Problem
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        v
Requirement & Constraint Analysis
        |
        v
Information / Source / Channel Model
        |
        v
Mathematical Analysis
        |
        v
Method / Coding Strategy Selection
        |
        v
Implementation / Simulation
        |
        v
Verification & Benchmarking
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        v
Engineering Result / Report

The agent should preserve assumptions, intermediate measurements, selected methods, verification evidence, limitations, and final results instead of returning an unexplained answer.

Design Principles

Engineering Agent, Not Study Bot

The primary purpose is to perform ITC engineering work. Teaching and explanations are secondary capabilities.

Offline First

Core mathematical analysis, deterministic algorithms, simulation, verification, and reporting should run locally without mandatory cloud services.

Verifiable Results

Numerical and algorithmic outputs should be reproducible and independently checkable wherever practical.

Explainable Decisions

When the agent selects a coding method or engineering strategy, it should record why it was selected and which constraints influenced the choice.

Modular Architecture

Information measures, source coding, channel analysis, error-control coding, simulation, verification, and reporting remain separable modules.

Autonomy With Evidence

Autonomy should not mean guessing. Decisions should be supported by explicit models, algorithms, constraints, tests, and verification evidence.

Initial Module Plan

itc_agent/
|-- agent/            # orchestration, planning, execution
|-- information/      # entropy and information measures
|-- sources/          # source models and statistics
|-- coding/           # source-coding algorithms
|-- channels/         # channel models and capacity analysis
|-- error_control/    # detection and correction methods
|-- simulation/       # experiments and noisy-channel simulation
|-- verification/     # mathematical and implementation checks
`-- reporting/        # reproducible engineering reports

Scope Boundaries

ITC Agent is not:

• a generic chatbot
• an RTU-only study application
• a notes repository
• a generic telecom assistant
• an LLM wrapper that merely generates plausible text

The project stays centered on computational and engineering work involving information theory, source coding, channel coding, coding theory, simulation, and verification.

Roadmap

M0 - Foundation

• define agent scope and engineering contracts
• deterministic result formats
• mathematical utilities
• testing and verification infrastructure

M1 - Information Analysis

• entropy
• conditional entropy
• joint entropy
• mutual information
• information content
• probability distribution validation

M2 - Source Coding

• prefix-code infrastructure
• Huffman coding
• Shannon-Fano coding
• efficiency and redundancy metrics
• encode/decode verification

M3 - Channel Analysis

• discrete channel models
• transition matrices
• channel statistics
• mutual-information analysis
• channel-capacity workflows

M4 - Error-Control Coding

• error-detection foundations
• block-code models
• coding-distance analysis
• encoder/decoder interfaces
• correction verification

M5 - Simulation & Benchmarking

• noisy-channel simulation
• repeatable experiments
• coding-scheme comparison
• reliability and performance reports

M6 - Autonomous ITC Agent

• requirement interpretation
• task planning
• automatic method selection
• multi-stage engineering workflows
• automatic verification
• technical report generation

Project Status

Early-stage / foundation phase.

Capabilities listed above are targets until their implementations and tests exist in the repository.

Contributing

Contributions are welcome in information-theory algorithms, coding-theory implementations, mathematical verification, channel simulation, agent orchestration, benchmarking, testing, and documentation.

Prefer small, independently testable engineering modules over large opaque implementations.

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ITC Agent aims to provide a practical and verifiable Information Theory and Coding capability that can perform specialist engineering work locally when a dedicated ITC engineer is unavailable.