Long-term investment thrives when agents remain within Green or Jernih zones for 60% of time, even with moderate payoffs.
Yellow zones, though ambiguous, often precede either zone collapse (into Red/Black) or repair (into Green), depending on agent patience and memory span.
Short-term focused agents underperform in total return compared to those with long-term memory-weighted valuation functions.
Introduction of ambiguous signaling leads to bifurcation in system behavior: one group drifts into mutual distrust (Red/Black), while others evolve emergent reputational equilibrium.
Institutions acting as contextual stabilizers (e.g., norm enforcement or reputation platforms) reduce relational entropy and catalyze higher investment consistency.
6. Interpretation and Theoretical Implications
These simulations reveal that relational zones function as economic attractors, guiding strategy not just via material expectations but through relational thermodynamics: systems tend toward zones that either stabilize (Green/Jernih) or spiral into conflict (Red/Black), contingent on memory, ambiguity tolerance, and future-orientation.
This challenges conventional financial modeling assumptions, suggesting that:
Time-consistent discounting may misrepresent real investor behavior in volatile relational zones,
Trust and betrayal costs should be treated as economic variables, not moral or psychological residuals,
Institutional design should account not only for information asymmetry but also for relational trajectory stabilization.
B. Multi-Zone Agent Simulation in Multinational Negotiation
1. Rationale
Traditional economic models of international negotiation --- whether on trade agreements, debt restructuring, or environmental treaties --- often assume rational agents optimizing national payoffs under fixed preferences and strategic transparency. However, real-world multilateral negotiations are entangled with strategic ambiguity, relational memory, power asymmetry, and shifting alliances. The Relational Zone Economics (RZE) framework models these dynamics through evolving zones, allowing for better representation of phenomena such as trust erosion, silent defection, and future-oriented repositioning.
2. Simulation Design
a. Agent Types:
Nation-states: With strategic interests encoded as multi-dimensional vectors (economic, political, environmental).
Transnational institutions: Mediators or rule enforcers with limited coercive power.
Non-state actors (optional): NGOs, lobby groups, media influencing perceived zone shifts.
b. Negotiation Space:
Each issue (e.g., tariffs, climate finance, IP rights) has a zone matrix, reflecting the relational climate between participating agents.
Each dyad or multilateral coalition operates under a zone configuration:
Z(t)={Zij(t)},Zij{White, Green, Yellow, Red, Black, Jernih}Z(t) = \{Z_{ij}(t)\}, \quad Z_{ij} \in \{\text{White, Green, Yellow, Red, Black, Jernih}\}
