OTTO v5.0.0-beta: From Heuristics to Real Learning

What's New in v5.0.0-beta

OTTO's cognitive routing pipeline now genuinely learns from outcomes. The trail->routing feedback loop that existed as dead code has been activated, outcome tracking added for all 7 modes, and heuristic weights replaced with UCB1 (a deterministic bandit algorithm with provable regret bounds).

Highlights

Feedback Loop Activated (Phase A)

• compute_trail_adjustments() was defined but never called in production — now wired into both CLI nudge and the background scheduler
• Plasticity amplification (2x during RED burnout) wired into trail deposits for done and park commands
• 200+ lines of existing dead code activated with ~20 lines of new wiring

Honest Naming (Phase B)

• _kahan_decay -> _exponential_decay (no Kahan summation was involved)
• "pheromone trail" -> "outcome trail" everywhere
• "stigmergic learning" -> "trail-based preference learning"
• Zero behavior change, pure credibility improvement

Outcome Tracking (Phase C)

• New mode_outcomes SQLite table records empirical mode effectiveness
• record_outcome(), get_mode_stats(), get_success_rate(), get_total_outcomes() API
• CLI done -> success, park -> mixed, nudge -> activated outcomes

UCB1 Mode Weighting (Phase D)

• New learner.py: Upper Confidence Bound algorithm (Auer et al. 2002)
• Deterministic: same outcome data -> same scores (He2025 compatible)
• Exploration bonus rewards under-tested modes
• Safety floors NEVER overridden — adjustments clamped to +/-0.2

Metrics Visibility (Phase E)

• New otto metrics command shows outcome counts, success rates, UCB adjustments, trail stats

Test Results

• 600 tests passing (up from 519 baseline)
• 0 regressions
• Python 3.11+ (developed on 3.14)

Breaking Changes

• _kahan_decay() renamed to _exponential_decay() (internal API, unlikely to affect consumers)
• Trail docstrings changed from "pheromone" to "outcome" terminology

Architecture

MESSAGE IN -> DETECT -> STORE -> SCHEDULE -> NUDGE
                                    |
                              [UCB1 Learning]
                              outcome_data -> compute_ucb_adjustments()
                                    |
                              trail_adjustments -> route_and_execute()
                                    |
                              [Constitutional Gate] <- safety floors NEVER modified
                                    |
                              OUTPUT (or suppress)

What's Next (v5.1)

• WhatsApp outbound transport
• Optional LLM-powered response generation
• User study: does self-suppression improve outcomes?

Full Changelog: v4.0.0...v5.0.0-beta