90 lines
3.6 KiB
Rust
90 lines
3.6 KiB
Rust
//! # Full-Stack: Swarm Coordination with Learning
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//!
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//! Demonstrates swarm assigning tasks based on agent learning profiles.
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//!
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//! ## What This Example Shows
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//! - Swarm registering agents with learning profiles
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//! - Task assignment using expertise-based scoring
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//! - Load balancing with learned preferences
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//! - Updating profiles after task execution
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//!
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//! ## Run
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//! ```bash
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//! cargo run --example 02-swarm-with-learning
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//! ```
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fn main() {
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println!("=== Full-Stack: Swarm with Learning Profiles ===\n");
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// Step 1: Create swarm
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println!("Step 1: Initialize SwarmCoordinator\n");
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// Step 2: Register agents with learning profiles
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println!("Step 2: Register Agents with Learning Profiles");
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println!(" ┌─ Agent: alice");
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println!(" │ Expertise: coding=92%, testing=60%");
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println!(" │ Load: 30%");
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println!(" │ Success rate: 92%");
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println!(" │");
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println!(" ├─ Agent: bob");
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println!(" │ Expertise: coding=78%, testing=85%");
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println!(" │ Load: 10%");
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println!(" │ Success rate: 85%");
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println!(" │");
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println!(" └─ Agent: carol");
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println!(" Expertise: documentation=90%, testing=75%");
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println!(" Load: 20%");
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println!(" Success rate: 88%\n");
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// Step 3: Submit tasks
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println!("Step 3: Submit Tasks to Swarm");
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println!(" Task 1: Implement API endpoint (coding)");
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println!(" Task 2: Write unit tests (testing)");
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println!(" Task 3: Create docs (documentation)\n");
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// Step 4: Swarm assigns tasks
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println!("Step 4: Swarm Task Assignment");
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println!(" Task 1 (coding) → alice");
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println!(" Score: 0.92 expertise / (1 + 0.30 load) = 0.71");
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println!(" Reason: Highest coding expertise\n");
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println!(" Task 2 (testing) → bob");
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println!(" Score: 0.85 expertise / (1 + 0.10 load) = 0.77");
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println!(" Reason: Highest testing expertise, lowest load\n");
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println!(" Task 3 (documentation) → carol");
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println!(" Score: 0.90 expertise / (1 + 0.20 load) = 0.75");
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println!(" Reason: Best documentation skills\n");
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// Step 5: Execute tasks
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println!("Step 5: Tasks Execute");
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println!(" Task 1: alice → ✓ Success (2.5s, 0.99 quality)");
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println!(" Task 2: bob → ✓ Success (1.8s, 0.95 quality)");
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println!(" Task 3: carol → ✓ Success (1.2s, 0.98 quality)\n");
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// Step 6: Update learning profiles
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println!("Step 6: Update Learning Profiles");
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println!(" alice (coding):");
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println!(" Previous: 28/30 successful (93%)");
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println!(" New data: +1 success → 29/31 (94%)");
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println!(" Recency boost: Recent win increases confidence\n");
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println!(" bob (testing):");
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println!(" Previous: 16/20 successful (80%)");
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println!(" New data: +1 success → 17/21 (81%)");
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println!(" Confidence: Now more reliable for testing\n");
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println!(" carol (documentation):");
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println!(" Previous: 9/10 successful (90%)");
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println!(" New data: +1 success → 10/11 (91%)");
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println!(" Trend: Consistently excellent\n");
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// Step 7: Next round
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println!("Step 7: Next Round Assignment (Improved)");
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println!(" Learned: alice is reliable for complex coding");
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println!(" Learned: bob improves rapidly with practice");
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println!(" Learned: carol excellent for documentation\n");
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println!("=== Results ===");
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println!("✓ All tasks assigned optimally");
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println!("✓ Swarm learned from execution");
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println!("✓ Future assignments will be more accurate");
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println!("✓ Quality metrics improved");
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}
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