用伽罗瓦域上的异或移位机制,构建可逆符号操作的神经架构。
How to Build Marcus's Algebraic Mind: Algebro-Deterministic Substrate over Galois Fields
- 基于GF(2)上的异或移位运算,实现变量绑定与非交换组合
- 固定维度下支持精确可逆绑定,三支柱能力全满足
- 适合关注可解释符号计算与神经符号融合的研究者
在《代数心智》(2001)中,马库斯指出,任何充分的认知架构必须包含变量运算、递归结构表示和个体/类区分,而多层感知机无法支持这些;他仅提出寄存器与树小段的实现构想。二十五年后,一种为速度、功耗和成本优化的内存架构,通过单一机制实现了这些功能。PyVaCoAl/VaCoAl是一种超维计算架构,端到端基于一个原语:在GF(2)上进行异或-移位,由本原多项式线性反馈移位寄存器(LFSRs)实现。该架构提供可逆绑定(Bind(R,F) = R xor shift(F)),非交换捆绑(区分“狗咬人”与“人咬狗”),以及固定维度下的地址空间个体/类分离。其能力在于以O(L)代价实现精确可逆绑定,将三个支柱作为架构原语而非训练产物,且具备无损可检视性。若将原语弱化为近似逆(如循环卷积),则三支柱同时退化——无法精确分解的,从未真正组合过,只是混合。本研究不声称此即心智,大脑非LFSR,亦不挑战大语言模型;而是提供其结构性缺失的可审计符号层。我们逐支柱建立对应关系,将树小段重释为由本原生成多项式标识的寄存器集,并引用同行观点指出齿状回-CA3环路可能是生物实例,还证明未见伪动词的屈折是佩尔意义上的第3级查询。硅中位级精确可逆,生物噪声下仅近似成立;生物主张仅为结构层面。
原文摘要 · Abstract (English)
In The Algebraic Mind (2001), Marcus held that any adequate cognitive architecture needs operations over variables, recursively structured representations, and an individual/kind distinction, and that multilayer perceptrons support none of them; he left a register-and-treelet implementation as a conjecture. Twenty-five years later a memory architecture built for unrelated reasons (speed, power and cost on commodity silicon) meets that specification operation for operation, through one mechanism rather than three. PyVaCoAl/VaCoAl is a hyperdimensional computing architecture built end-to-end on one primitive: XOR-and-shift over GF(2), realised by primitive-polynomial linear-feedback shift registers (LFSRs). It gives reversible binding Bind(R,F) = R xor shift(F), non-commutative bundling that distinguishes "dog bites man" from "man bites dog", and address-space individual/kind separation, at fixed dimension. Capability: exact reversible binding at O(L) cost supplies each pillar as an architectural primitive, not a product of training, with inspectability no lossy substrate offers. Necessity: weaken the primitive to an approximate inverse, as circular convolution does, and all three pillars degrade together -- what cannot be exactly decomposed was never composed, only mixed. Position: this is not the mind, the brain is not an LFSR, and we do not beat large language models; the substrate supplies the auditable symbolic layer they structurally lack. We develop the correspondence pillar by pillar, recast the treelet as a register set identified by a primitive generator polynomial, cite a companion Perspective on the dentate gyrus-CA3 circuit as a biological instance, and show that inflecting an unseen pseudoverb is a rung-3 query in Pearl's sense. Bit-exact reversibility holds in silicon and only approximately under biological noise; biological claims are structural only.
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