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71 lines
3.8 KiB
TeX
71 lines
3.8 KiB
TeX
\section{Game-Theoretic Analysis}
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\label{sec:game}
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\subsection{Validator Participation Game}
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We define the participation game $\Gamma = (\mathcal{N}, \{A_i\}, \{U_i\})$ where:
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\begin{itemize}
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\item $\mathcal{N} = \{1, \ldots, N\}$: potential validators
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\item $A_i = \{0\} \cup [s^{\min}_{\text{val}}, s_i^{\max}]$: action space (stake 0 or $\geq s^{\min}_{\text{val}}$)
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\item $U_i$: utility function
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\end{itemize}
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\begin{definition}[Validator Utility]
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\begin{equation}
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U_i(s_i, s_{-i}) = \underbrace{r_i^{\text{self}}(s_i, s_{-i})}_{\text{self-stake reward}} + \underbrace{r_i^{\text{commission}}(s_i, s_{-i})}_{\text{commission income}} - \underbrace{h_i}_{\text{hardware cost}} - \underbrace{s_i \cdot r_{\text{opp}}}_{\text{opportunity cost}} - \underbrace{\mathbb{E}[\text{slash}_i]}_{\text{expected slashing}}
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\end{equation}
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\end{definition}
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\subsection{Honest Validation as Dominant Strategy}
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\begin{theorem}[Incentive Compatibility]\label{thm:ic}
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For a validator $v_i$ with $s_i < W/3$, honest participation is a strictly dominant strategy when:
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\begin{equation}
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r_i^{\text{total}} > h_i + s_i \cdot r_{\text{opp}} + \max_{\text{attack}} \left(\pi_{\text{attack}} - p_{\text{slash}} \cdot s_i \cdot p_{\text{detect}}\right)
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\end{equation}
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where $\pi_{\text{attack}}$ is the maximum extractable value from any attack and $p_{\text{detect}}$ is the detection probability.
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\end{theorem}
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\begin{proof}
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The utility from honest behavior is $U^H_i = r_i^{\text{total}} - h_i - s_i \cdot r_{\text{opp}}$. The utility from any Byzantine strategy is:
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\begin{equation}
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U^B_i = r_i^{\text{total}} + \pi_{\text{attack}} \cdot (1 - p_{\text{detect}}) - p_{\text{slash}} \cdot s_i \cdot p_{\text{detect}} - h_i - s_i \cdot r_{\text{opp}}
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\end{equation}
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For equivocation, $p_{\text{detect}} = 1$ (cryptographically provable), so:
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\begin{equation}
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U^B_i - U^H_i = \pi_{\text{attack}} \cdot 0 - 0.05 \cdot s_i < 0
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\end{equation}
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For coordinated attacks requiring $\geq W/3$ stake, $v_i$ alone (with $s_i < W/3$) cannot mount the attack. Collusion with others introduces the free-rider problem: each participant bears the full slashing risk but shares the attack profit, making defection (honest behavior) individually rational.
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\end{proof}
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\subsection{Delegation Market Equilibrium}
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\begin{theorem}[Delegation Equilibrium]
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In a market with $n$ validators and $M$ total delegatable tokens, the equilibrium delegation allocation satisfies:
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\begin{equation}
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\frac{s_d^*}{M} = \frac{(1 - c_i) \cdot u_i}{\sum_j (1 - c_j) \cdot u_j} \quad \text{for delegators of } v_i
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\end{equation}
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That is, delegation flows proportionally to the after-commission, uptime-adjusted return.
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\end{theorem}
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\begin{proof}
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A rational delegator maximizes expected return $(1 - c_i) \cdot u_i \cdot R / W$. In equilibrium, all validators offer the same marginal return to delegators. If validator $i$ offers higher marginal return, it attracts delegation until marginal returns equalize (diminishing returns from increased $W$).
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\end{proof}
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\subsection{Entry and Exit Dynamics}
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\begin{proposition}[Free Entry Equilibrium]
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The equilibrium number of validators $n^*$ satisfies:
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\begin{equation}
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n^* = \left\lfloor \frac{R_t \cdot c^{\min}}{h^{\text{avg}} + s^{\min}_{\text{val}} \cdot r_{\text{opp}}} \right\rfloor
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\end{equation}
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where $h^{\text{avg}}$ is the average hardware cost per epoch.
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\end{proposition}
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\begin{proof}
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Entry occurs when $U_i > 0$; exit occurs when $U_i < 0$. At the margin, the least profitable validator earns zero profit: commission income equals costs. With $n$ validators each earning approximately $R_t / n$ in base rewards, the marginal validator earns $c^{\min} \cdot R_t / n$ in commission. Setting this equal to $h + s^{\min}_{\text{val}} \cdot r_{\text{opp}}$ and solving for $n$ yields the result.
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\end{proof}
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