Multi-Paradigm Problem Solving

Overview

Multi-Paradigm Problem Solving enables platform agents to apply multiple problem-solving paradigms to complex challenges. Rather than constraining agents to a single computational model, the Prismatic Platform embraces the insight that different problem domains respond optimally to different computational paradigms. Agents combine functional programming patterns, logical reasoning, heuristic approaches, graph-based analysis, and formal verification methods to achieve solutions that no single paradigm could deliver alone.

This capability is foundational to the platform's approach to Intelligence Synthesis, where real-world problems rarely conform to a single analytical model. A compliance assessment, for instance, may require functional data transformations, logical rule evaluation, graph traversal for entity relationships, and formal proofs for regulatory completeness -- all within a single investigation workflow.

The multi-paradigm approach is not eclecticism. It is a structured capability where paradigm selection is governed by problem characteristics, agent tier authority, and quality requirements. Each paradigm has defined strengths, known limitations, and measurable performance characteristics. The platform's paradigm selection protocol matches problems to paradigms based on empirical evidence, not arbitrary preference.

Paradigm Catalog

The platform supports six distinct problem-solving paradigms, each implemented through Elixir/OTP's capabilities and extended through specialized libraries and formal tools.

Functional Programming

The platform's Elixir/OTP foundation makes functional programming the default paradigm. Pure functions, immutable data structures, and composable transformations provide the backbone for data processing pipelines.

# Functional pipeline for OSINT entity enrichment
defmodule PrismaticOsint.EntityEnrichment do
  @moduledoc """
  Pure functional pipeline for entity enrichment.
  Each stage is a pure transformation with no side effects.
  """

  @spec enrich(entity()) :: {:ok, enriched_entity()} | {:error, term()}
  def enrich(entity) do
    entity
    |> normalize_identifiers()
    |> resolve_aliases()
    |> enrich_from_registries()
    |> score_risk_factors()
    |> validate_through_trinity_gate()
  end

  defp normalize_identifiers(%{identifiers: ids} = entity) do
    normalized = Enum.map(ids, &Identifier.normalize/1)
    %{entity | identifiers: normalized}
  end

  defp score_risk_factors(entity) do
    risk_score =
      entity.signals
      |> Enum.map(&Signal.risk_weight/1)
      |> Enum.sum()
      |> normalize_score()

    Map.put(entity, :risk_score, risk_score)
  end
end

OTP Concurrency Patterns

OTP provides the concurrency paradigm through lightweight processes, message passing, and supervision trees. This paradigm excels at problems requiring parallel execution, fault isolation, and stateful coordination.

# Parallel OSINT collection with timeout and fault isolation
defmodule PrismaticOsint.ParallelCollector do
  @moduledoc """
  Concurrent data collection across multiple OSINT sources.
  Uses Task.async_stream for parallel execution with timeout.
  """

  @timeout_ms 30_000

  @spec collect(list(source()), query()) :: list(result())
  def collect(sources, query) do
    sources
    |> Task.async_stream(
      fn source -> source.adapter.fetch(query) end,
      max_concurrency: 10,
      timeout: @timeout_ms,
      on_timeout: :kill_task
    )
    |> Enum.reduce([], fn
      {:ok, {:ok, data}}, acc -> [data | acc]
      {:ok, {:error, _reason}}, acc -> acc
      {:exit, _reason}, acc -> acc
    end)
    |> Enum.reverse()
  end
end

Graph-Based Reasoning

Entity relationships, dependency chains, and knowledge networks require graph-based reasoning. The platform uses KuzuDB for persistent graph queries and in-memory graph algorithms for real-time analysis.

Formal Verification

The White Team agents employ formal verification through Lean4 theorem proving, property-based testing, and contract validation. This paradigm provides mathematical certainty where heuristic approaches offer only probabilistic confidence.

Epistemic Reasoning

NABLA Infinity provides the epistemic paradigm where agents reason about uncertainty, confidence, and belief revision. This paradigm governs how the platform handles incomplete or contradictory information.

Heuristic Pattern Recognition

For problems where formal methods are impractical and pure functional approaches lack domain knowledge, heuristic pattern recognition applies learned patterns from historical data to current situations.

Paradigm Selection Protocol

The platform does not randomly apply paradigms. A structured selection protocol matches problem characteristics to optimal paradigm combinations.

Problem Input --> Complexity Assessment --> Paradigm Selection --> Execute --> Validate
     |                  |                       |                   |           |
  Classify         Measure              Pick optimal          Apply      Trinity
  domain          constraints           approach(es)        solution      Gate

Selection Criteria

Combined Paradigm Example

A typical EASM security assessment demonstrates multi-paradigm synergy.

Agent Tier Integration

Paradigm availability is governed by the AIAD Standard tier system, ensuring that complex multi-paradigm operations are coordinated by appropriately authorized agents.

L3 agents serve as orchestrators, decomposing complex problems into paradigm-specific sub-tasks and delegating to L1/L2 agents with the appropriate specialization. This ensures that multi-paradigm operations maintain coherent coordination while leveraging specialized execution at each step.

Quality Enforcement

Every paradigm application passes through the platform's quality infrastructure.

Performance and Metrics

Configuration

Paradigm selection behavior and availability can be configured per agent tier and per domain context.

# config/config.exs
config :prismatic_agents, PrismaticAgents.ParadigmSelector,
  default_paradigm: :functional,
  max_paradigms_per_operation: 4,
  formal_verification_enabled: true,
  heuristic_confidence_floor: 0.7,
  paradigm_timeout_ms: 30_000,
  selection_strategy: :evidence_based

config :prismatic_agents, PrismaticAgents.ParadigmMonitor,
  track_selection_accuracy: true,
  report_interval: :timer.minutes(15),
  alert_on_fallback: true,
  performance_baseline_window: :timer.hours(24)

Integration

• Applied through NABLA Axioms for epistemic problems
• Validated by Trinity Gate formal verification for all conclusions
• Powered by Telemetry Integration for paradigm performance tracking
• Governed by NO DOUBTS evidence requirements for paradigm selection
• Quality enforced by NO MERCY zero-tolerance standards
• Supports Autonomous Self-Healing through multi-paradigm diagnostic analysis
• Feeds Intelligence Synthesis with paradigm-appropriate analytical outputs
• Tier-governed by AIAD Standard authority definitions
• Compliance verified by AIAD Compliance
• Monitored by Real-Time Monitoring for operational metrics
• Quality Gates enforce paradigm-specific quality requirements
• Cross-Domain Flexibility enables paradigm application across domains
• Color Teams White Team provides formal verification paradigm

Connect & Contribute

Created by Tomáš Korcak (korczis) | Open Source under GHL

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