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21 lines
1.8 KiB
TeX
21 lines
1.8 KiB
TeX
\section{Related Work}
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\label{sec:related}
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\subsection{Automated Market Makers}
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Uniswap~\cite{adams2020uniswap,adams2021uniswapv3} pioneered the constant product formula $xy = k$ and later introduced concentrated liquidity. Curve~\cite{egorov2019stableswap} introduced the stableswap invariant for correlated assets. Balancer~\cite{martinelli2019balancer} generalized to weighted pools. Bancor~\cite{hertzog2017bancor} introduced single-sided liquidity. CrocSwap~\cite{crocswap2023} explored ambient liquidity. None of these address multi-dimensional resource pricing with quality constraints.
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\subsection{Decentralized Compute Markets}
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Golem~\cite{golem2016} and iExec~\cite{iexec2018} pioneered decentralized compute with orderbook-based pricing. Akash~\cite{akash2020} uses reverse auctions. Render Network~\cite{rendernetwork2021} focuses on GPU rendering. Gensyn~\cite{gensyn2023} targets ML training verification. io.net~\cite{ionet2024} aggregates GPU clusters. None employ physics-inspired AMM mechanisms for pricing.
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\subsection{Physics-Inspired Market Design}
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The application of statistical mechanics to financial markets has a rich history~\cite{mantegna2000introduction,bouchaud2003theory}. Geometric approaches to option pricing using differential geometry were explored by~\cite{ilinski2001physics}. Hamiltonian methods in optimal control and economics appear in~\cite{sethi2019optimal}. Our contribution is the first application of symplectic geometry to AMM design.
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\subsection{Verifiable Computation}
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TrueBit~\cite{teutsch2019truebit} introduced verification games for off-chain computation. zkEVM~\cite{zkevm2023} provides zero-knowledge proofs of EVM execution. TEE-based attestation~\cite{costan2016intel} offers hardware-rooted trust. Our PoAI mechanism combines TEE attestations with statistical sampling for efficient verification of AI workloads.
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