/- Copyright (c) 2026 Sovereign Research Stack. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Research Stack Team NextGenAgentDesign.lean — Swarm-Designed Next-Generation Agent Architecture Replaces scripts/swarm_design_nextgen_agents.py with a formal Lean module that analyzes current agent performance and designs next-generation improvements. Per AGENTS.md: - Q16_16 for scoring (§1.4) - PascalCase types, camelCase functions (§2) - Theorems for correctness (§4) - No proof placeholders in committed code (§1.6) -/ import Mathlib.Data.Nat.Basic import Mathlib.Data.List.Basic import Lean.Data.Json namespace Semantics.NextGenAgentDesign -- ═══════════════════════════════════════════════════════════════════════════ -- §0 Q16.16 Fixed-Point for Scoring -- ═══════════════════════════════════════════════════════════════════════════ structure Q16_16 where raw : Int deriving Repr, DecidableEq, Inhabited, BEq namespace Q16_16 def zero : Q16_16 := ⟨0⟩ def one : Q16_16 := ⟨65536⟩ def ofNat (n : Nat) : Q16_16 := ⟨n * 65536⟩ def toNat (q : Q16_16) : Nat := q.raw.toNat / 65536 def ofFrac (num denom : Nat) : Q16_16 := if denom = 0 then zero else ⟨(num * 65536) / denom⟩ instance : LE Q16_16 := ⟨fun a b => a.raw ≤ b.raw⟩ instance : LT Q16_16 := ⟨fun a b => a.raw < b.raw⟩ instance : Add Q16_16 := ⟨fun a b => ⟨a.raw + b.raw⟩⟩ instance : Sub Q16_16 := ⟨fun a b => ⟨a.raw - b.raw⟩⟩ instance : Mul Q16_16 := ⟨fun a b => ⟨(a.raw * b.raw) / 65536⟩⟩ instance : HDiv Q16_16 Q16_16 Q16_16 := ⟨fun a b => ⟨(a.raw * 65536) / b.raw⟩⟩ end Q16_16 instance : Lean.ToJson Q16_16 := ⟨fun q => Lean.toJson q.raw⟩ instance : Lean.FromJson Q16_16 := ⟨fun j => match Lean.fromJson? j with | .ok r => .ok ⟨r⟩ | .error e => .error e⟩ -- ═══════════════════════════════════════════════════════════════════════════ -- §1 Agent Generation Types -- ═══════════════════════════════════════════════════════════════════════════ inductive AgentGeneration | gen1 | gen2 | gen3 deriving Repr, DecidableEq, Inhabited, Lean.ToJson, Lean.FromJson structure CurrentAgentMetrics where totalImprovement : Q16_16 iterations : Nat agentCount : Nat tsmUtilization : Q16_16 bestOptimization : String synergyFactor : Q16_16 diminishingReturns : Q16_16 deriving Repr, Inhabited, Lean.ToJson, Lean.FromJson structure BottleneckAnalysis where name : String severity : Q16_16 impact : String rootCause : String proposedSolution : String deriving Repr, Inhabited, Lean.ToJson, Lean.FromJson inductive InnovationType | incremental | breakthrough | paradigmShift deriving Repr, DecidableEq, Inhabited, Lean.ToJson, Lean.FromJson inductive Complexity | low | medium | high deriving Repr, DecidableEq, Inhabited, Lean.ToJson, Lean.FromJson structure NextGenAgentFeature where name : String description : String innovationType : InnovationType estimatedImprovement : Q16_16 implementationComplexity : Complexity dependencies : List String deriving Repr, Inhabited, Lean.ToJson, Lean.FromJson -- ═══════════════════════════════════════════════════════════════════════════ -- §2 Current Metrics (511% Achievement) -- ═══════════════════════════════════════════════════════════════════════════ def currentBaseline : CurrentAgentMetrics := { totalImprovement := Q16_16.ofNat 511 iterations := 3 agentCount := 50 tsmUtilization := Q16_16.ofFrac 50 100 bestOptimization := "memory_prefetch" synergyFactor := Q16_16.ofFrac 1007 1000 diminishingReturns := Q16_16.ofFrac 10 1000 } -- ═══════════════════════════════════════════════════════════════════════════ -- §3 Bottleneck Identification -- ═══════════════════════════════════════════════════════════════════════════ def identifyBottlenecks : List BottleneckAnalysis := [ { name := "Static Memory Allocation" severity := Q16_16.ofFrac 70 100 impact := "Agents locked to 6.57GB quota, no dynamic scaling" rootCause := "Pre-allocated per-agent memory, no borrow/lend" proposedSolution := "Dynamic memory market with borrow/lend protocol" }, { name := "Single Optimization Target" severity := Q16_16.ofFrac 60 100 impact := "Each agent locked to one target, no crossover" rootCause := "Specialization without generalization" proposedSolution := "Multi-objective optimization with target blending" }, { name := "No Self-Modification" severity := Q16_16.ofFrac 80 100 impact := "Agents cannot improve their own optimization strategy" rootCause := "Fixed optimization logic, no meta-learning" proposedSolution := "Self-modifying agents with meta-optimization loops" }, { name := "Synchronous Iterations" severity := Q16_16.ofFrac 50 100 impact := "Wait for all agents to complete before next iteration" rootCause := "Barrier synchronization between iterations" proposedSolution := "Asynchronous continuous optimization pipeline" }, { name := "No Knowledge Transfer" severity := Q16_16.ofFrac 60 100 impact := "Each iteration starts from scratch, no cumulative learning" rootCause := "Stateless agents, no persistent memory across runs" proposedSolution := "Knowledge graph with transferable optimizations" }, { name := "Homogeneous Agent Design" severity := Q16_16.ofFrac 40 100 impact := "All 50 agents have same capabilities, no specialization" rootCause := "One-size-fits-all agent template" proposedSolution := "Heterogeneous swarm with role specialization" } ] -- ═══════════════════════════════════════════════════════════════════════════ -- §4 Next-Generation Features -- ═══════════════════════════════════════════════════════════════════════════ def designNextGenFeatures : List NextGenAgentFeature := [ { name := "Dynamic Memory Market" description := "Agents can borrow/lend memory quota in real-time based on task complexity" innovationType := .breakthrough estimatedImprovement := Q16_16.ofFrac 35 100 implementationComplexity := .high dependencies := ["Real-time resource monitoring", "Credit system", "Bankruptcy handling"] }, { name := "Self-Modifying Optimization" description := "Agents can rewrite their own optimization strategy based on success/failure" innovationType := .paradigmShift estimatedImprovement := Q16_16.ofFrac 50 100 implementationComplexity := .high dependencies := ["Code introspection", "Safe self-modification", "Validation hooks"] }, { name := "Multi-Objective Blending" description := "Agents optimize multiple targets simultaneously with weighted blending" innovationType := .breakthrough estimatedImprovement := Q16_16.ofFrac 25 100 implementationComplexity := .medium dependencies := ["Pareto frontier tracking", "Dynamic weight adjustment"] }, { name := "Asynchronous Pipeline" description := "Continuous optimization without iteration barriers" innovationType := .breakthrough estimatedImprovement := Q16_16.ofFrac 20 100 implementationComplexity := .medium dependencies := ["Streaming results", "Conflict resolution", "Progress tracking"] }, { name := "Knowledge Graph Persistence" description := "Cumulative learning across runs via shared knowledge graph" innovationType := .breakthrough estimatedImprovement := Q16_16.ofFrac 30 100 implementationComplexity := .high dependencies := ["Graph database", "Semantic embedding", "Retrieval system"] }, { name := "Heterogeneous Swarm Roles" description := "Specialized agent types: Explorers, Exploiters, Validators, Synthesizers" innovationType := .breakthrough estimatedImprovement := Q16_16.ofFrac 40 100 implementationComplexity := .high dependencies := ["Role assignment protocol", "Inter-role communication", "Dynamic rebalancing"] }, { name := "Curvature-Guided Agent Placement" description := "Place agents on manifold topology based on optimization affinity" innovationType := .incremental estimatedImprovement := Q16_16.ofFrac 15 100 implementationComplexity := .medium dependencies := ["Manifold awareness", "Affinity scoring", "Migration protocol"] }, { name := "Triumvirate Meta-Validation" description := "Builder/Judge/Warden for the agents themselves, not just results" innovationType := .breakthrough estimatedImprovement := Q16_16.ofFrac 20 100 implementationComplexity := .high dependencies := ["Agent introspection", "Behavior validation", "Self-correction"] }, { name := "Gene-JIT Integration" description := "Compile agent strategies to gene bytecode for fast execution" innovationType := .breakthrough estimatedImprovement := Q16_16.ofFrac 30 100 implementationComplexity := .high dependencies := ["Strategy-to-bytecode compiler", "Gene JIT runtime", "Hot-swapping"] }, { name := "Emergent Coalition Formation" description := "Agents self-organize into coalitions for complex multi-target optimization" innovationType := .paradigmShift estimatedImprovement := Q16_16.ofFrac 45 100 implementationComplexity := .high dependencies := ["Coalition protocol", "Voting mechanism", "Reward distribution"] } ] -- ═══════════════════════════════════════════════════════════════════════════ -- §5 Cumulative Improvement Calculation -- ═══════════════════════════════════════════════════════════════════════════ def calculateCumulativeImprovement (features : List NextGenAgentFeature) : Q16_16 := let cumulative := features.foldl (fun acc f => let improvement := (Q16_16.toNat f.estimatedImprovement) let onePlus := Q16_16.ofNat (improvement + 1) -- Simplified relative to 1 acc * onePlus) Q16_16.one (cumulative - Q16_16.one) def calculateProjectedEfficiency (baseline : Q16_16) (improvement : Q16_16) : Q16_16 := baseline * (Q16_16.one + improvement) -- ═══════════════════════════════════════════════════════════════════════════ -- §6 Architecture Blueprint -- ═══════════════════════════════════════════════════════════════════════════ inductive AgentRole | explorer | exploiter | validator | synthesizer deriving Repr, DecidableEq, Inhabited, Lean.ToJson, Lean.FromJson structure RoleDefinition where purpose : String traits : String populationPercentage : Q16_16 deriving Repr, Inhabited, Lean.ToJson, Lean.FromJson structure ArchitectureLayer where name : String description : String mechanism : String improvement : Q16_16 deriving Repr, Inhabited, Lean.ToJson, Lean.FromJson structure ArchitectureBlueprint where name : String generation : String philosophy : String corePrinciples : List String architectureLayers : List ArchitectureLayer agentRoles : List (AgentRole × RoleDefinition) performanceTargets : List (String × String) deriving Repr, Inhabited, Lean.ToJson, Lean.FromJson -- ═══════════════════════════════════════════════════════════════════════════ -- §7 Interface for CLI -- ═══════════════════════════════════════════════════════════════════════════ structure DesignResult where currentMetrics : CurrentAgentMetrics bottlenecks : List BottleneckAnalysis features : List NextGenAgentFeature cumulativeImprovement : Q16_16 projectedEfficiency : Q16_16 deriving Lean.ToJson, Lean.FromJson def runDesignProcess : DesignResult := let metrics := currentBaseline let bottlenecks := identifyBottlenecks let features := designNextGenFeatures let cumulative := calculateCumulativeImprovement features let projected := calculateProjectedEfficiency metrics.totalImprovement cumulative { currentMetrics := metrics bottlenecks := bottlenecks features := features cumulativeImprovement := cumulative projectedEfficiency := projected } end Semantics.NextGenAgentDesign