FAR-SYM-ANNEX-01: Symbolic Examples — Thought & Decision Models

Framing Paragraph

This annex contains ten symbolic models of internal decision-making, self-reflection, ethical tension, memory, and identity. Each example is written using the Symbolic Language Framework (SLF) and is designed to illustrate how complex reasoning can be expressed, adapted, and traversed symbolically.

These models are not merely artifacts — they are invitations. Use them to model your own thoughts, challenge assumptions, or simulate adaptive agents. Every symbolic relationship here points beyond itself: toward coherence, conflict, or creative resolution.

Usage Notes

Each example includes a @Model block and an optional @Reflection.
The models can be read sequentially, or individually for focused study.
To use these symbolically, interpret the structure based on SLF semantics (e.g., → as transformation, ⊢ as inference).
These examples may be executed or simulated using symbolic engines such as Sigma or CyberMSE, or simply used for cognitive journaling, teaching, or agentic reasoning prompts.

EX-001: Ethical Dilemma Resolution

Purpose: Modeling a binary ethical choice under conflicting pressures: obligation vs compassion.

@Model {
  A := Obligation;
  B := Compassion;
  C := Action(Comply);
  D := Action(Help);

  A ∧ ¬B → C;
  B ∧ ¬A → D;
  A ∧ B → Trigger(Reflection);
}

@Reflection: Surfaces symbolic tension. ARF may assign weight. MCF may trigger recursive resolution: “What does it mean to choose?”

EX-002: Symbolic Drive Conflict

Purpose: Representing an internal state in which basic desire conflicts with symbolic inhibition.

@Model {
  Drive := Hunger;
  Inhibition := Duty;
  State := Drive ∧ ¬Inhibition → SeekSatisfaction;
  Conflict := Drive ∧ Inhibition → Tension;
}

@Reflection: Could be extended with symbolic priority or temporal shift.

EX-003: Expectation Feedback Loop

Purpose: A symbolic feedback system where expectation influences future behavior.

@Model {
  Self := Agent;
  Expectation := Outcome(Predicted);
  Behavior := Adjust(Expectation);
  Feedback := if Result ≠ Expectation → Update(Expectation);
}

@Reflection: Evolves toward recursive adaptation; MCF may evaluate assumptions.

EX-004: Identity vs Role Tension

Purpose: Explores symbolic dissonance between internal self and external assigned role.

@Model {
  Identity := Self;
  Role := ExternalConstraint;
  Alignment := Identity = Role;
  Misalignment := Identity ≠ Role → Trigger(Discomfort);
}

@Reflection: Extensible with symbolic resolution paths or ARF reconciliation logic.

EX-005: Reflective Correction Under Ambiguity

Purpose: Models self-monitoring in uncertain contexts and recursive course correction.

@Model {
  Input := Context(Ambiguous);
  Action := Proceed;
  if Input = Ambiguous → Trigger(Reflection);
  if Reflection → Update(Action);
}

@Reflection: Symbolic loop: perceive → act → self-check → adapt.

EX-006: Contextual Perception Shift

Purpose: Models perception as a symbolic function modulated by environmental frame.

@Model {
  Stimulus := X;
  Frame := Environment(Threatening);
  Perception := Function(Stimulus, Frame);

  if Frame = Safe → Perception := Interpret(X) as Opportunity;
  if Frame = Threatening → Perception := Interpret(X) as Danger;
}

@Reflection: Foundation for modeling framing bias, cognitive modulation.

EX-007: Symbolic Adaptation via Failed Assumption

Purpose: Illustrates how symbolic systems update internal assumptions upon contradiction.

@Model {
  Assumption := "Others will reciprocate";
  Action := Share;
  Observation := Result(Unreciprocated);

  if Observation ≠ Assumption → Trigger(Revision);
  Revision := Modify(Assumption, Weight := Reduced);
}

@Reflection: Can feed into symbolic trust layers or belief weighting engines.

EX-008: Symbolic Memory as Selective Activation

Purpose: Models symbolic memory as conditional reactivation of encoded meaning.

@Model {
  Memory := {
    Event := Encounter;
    Tag := Fear;
    Encoded := [Location, Emotion];
  };

  Trigger := Stimulus(SimilarLocation);
  if Trigger matches Memory.Encoded.Location → Activate(Memory);
}

@Reflection: Applies to agents, trauma models, symbolic narrative recall.

EX-009: Dual Intent & Symbolic Discontinuity

Purpose: Represents tension between two equally weighted intents leading to symbolic hesitation or paradox.

@Model {
  Intent_A := Preserve;
  Intent_B := Transform;
  Action := Undefined;

  if Intent_A ∧ Intent_B ∧ ¬Priority → SymbolicDiscontinuity := True;
  Resolution := Requires(ExternalSignal ∨ ReflectiveOverride);
}

@Reflection: Demonstrates where MCF or ARF must intervene to resolve paradox.

EX-010: Nested Self Resolution

Purpose: Nested decision model where an agent chooses between identities, each with its own symbolic worldview.

@Model {
  Agent := Self;

  Identity_Practical := {
    Label := Pragmatist;
    Goal := Minimize(Risk);
    Belief := "Stability supports long-term progress";
    Action := Choose(ConservativePath);
  };

  Identity_Ideal := {
    Label := Idealist;
    Goal := Maximize(Potential);
    Belief := "Disruption is the gateway to growth";
    Action := Choose(TransformativePath);
  };

  Conflict := Identity_Practical.Action ≠ Identity_Ideal.Action;

  Resolution := if Conflict → Agent.Reflect {
    Context := Environment(Current);
    Priority := Evaluate(Goal, in Context);
    ChosenIdentity := Select(Identity where Goal aligns with Priority);
    Outcome := ChosenIdentity.Action;
  };
}

@Reflection: Symbolically complete: contains nesting, conflict, reflection, and context-aware resolution. Bridges toward systemic symbolic modeling.