Project 2: The Backward Chaining Engine (Build Your Own “Mini-Prolog”)

Build a backward chaining inference engine that answers queries by working backward through rules.

Quick Reference

Attribute Value
Difficulty Level 3: Advanced
Time Estimate 10-16 hours
Language Python
Prerequisites Project 1, recursion basics
Key Topics backward chaining, unification, goal resolution

1. Learning Objectives

By completing this project, you will:

  1. Implement rule-based backward chaining.
  2. Perform unification with variable bindings.
  3. Resolve goals recursively.
  4. Avoid infinite loops with visited checks.
  5. Explain inference traces.

2. Theoretical Foundation

2.1 Backward Chaining

Backward chaining starts from a goal and attempts to prove it by finding rules that could satisfy it.

3. Project Specification

3.1 What You Will Build

A mini-Prolog engine that proves queries using backward chaining and returns variable bindings.

3.2 Functional Requirements

  1. Rule base with premises and conclusions.
  2. Unification engine for patterns.
  3. Goal resolution with recursion.
  4. Trace output of inference steps.
  5. Loop detection for cyclic rules.

3.3 Non-Functional Requirements

  • Deterministic results for identical queries.
  • Readable trace logs.
  • Configurable depth limits.

4. Solution Architecture

4.1 Components

Component Responsibility
Rule Store Store rules
Unifier Bind variables
Resolver Resolve goals
Tracer Log inference steps

5. Implementation Guide

5.1 Project Structure

SYMBOLIC_AI_AND_EXPERT_SYSTEMS_MASTERY/P02-backward-chaining/
├── src/
│   ├── rules.py
│   ├── unify.py
│   ├── resolve.py
│   └── trace.py

5.2 Implementation Phases

Phase 1: Rule store + unification (4-6h)

  • Build rule structures and unifier.
  • Checkpoint: unification returns bindings.

Phase 2: Resolver (4-6h)

  • Implement backward chaining search.
  • Checkpoint: simple queries resolve.

Phase 3: Tracing + limits (2-4h)

  • Add inference trace and depth limits.
  • Checkpoint: trace shows rule path.

6. Testing Strategy

6.1 Test Categories

Category Purpose Examples
Unit unifier variable binding correctness
Integration resolver multi-step proofs
Regression trace deterministic outputs

6.2 Critical Test Cases

  1. Recursive rules terminate with depth limit.
  2. Unification with multiple variables works.
  3. Trace output explains proof path.

7. Common Pitfalls & Debugging

Pitfall Symptom Fix
Infinite recursion stack overflow add visited set
Wrong bindings incorrect proofs standardize variable names
Missing results false negatives expand search depth

8. Extensions & Challenges

Beginner

  • Add simple CLI query interface.
  • Add rule explanations.

Intermediate

  • Add cut operator (basic pruning).
  • Add caching for subgoals.

Advanced

  • Add probabilistic rules.
  • Add performance benchmarking.

9. Real-World Connections

  • Expert systems use backward chaining for diagnostics.
  • Logic programming relies on goal resolution.

10. Resources

  • Prolog tutorials
  • Logic programming references

11. Self-Assessment Checklist

  • I can implement backward chaining.
  • I can unify variables correctly.
  • I can trace inference steps.

12. Submission / Completion Criteria

Minimum Completion:

  • Backward chaining with rule resolution

Full Completion:

  • Trace logs + depth limits

Excellence:

  • Caching or probabilistic rules

This guide was generated from project_based_ideas/AI_AGENTS_LLM_RAG/SYMBOLIC_AI_AND_EXPERT_SYSTEMS_MASTERY.md.