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