标题： 检查刺激等价模拟中的拒绝关系 显示英文标题

标题： Examining Reject Relations in Stimulus Equivalence Simulations

摘要： 模拟为探索刺激等价（SE）提供了有价值的工具，但拒绝关系可能干扰等价类形成的评估这一潜力存在争议。 本研究使用计算模型探讨了拒绝关系在刺激等价获得中的作用。 我们在匹配样本（MTS）模拟的18种条件下检查了前馈神经网络（FFNs）、来自变压器的双向编码器表示（BERT）和生成式预训练变压器（GPT）。 条件在训练结构（线性序列、一对一和多对一）、关系类型（仅选择、仅拒绝和选择-拒绝）以及负比较选择（标准和有偏）方面有所不同。 一个概率代理作为基准，体现了纯粹的联想学习。 主要目标是确定人工神经网络是否能表现出等价类形成，或者其表现是否反映了联想学习。 结果表明，拒绝关系影响了代理的表现。 虽然一些代理在等价测试中取得了高准确性，尤其是在有拒绝关系和有偏负比较的情况下，但这种表现与概率代理相当。 这些发现表明，人工神经网络，包括变压器模型，可能依赖于联想策略而非SE。 这强调了在等价的计算模型中需要仔细考虑拒绝关系和更严格的标准。 显示英文摘要

摘要： Simulations offer a valuable tool for exploring stimulus equivalence (SE), yet the potential of reject relations to disrupt the assessment of equivalence class formation is contentious. This study investigates the role of reject relations in the acquisition of stimulus equivalence using computational models. We examined feedforward neural networks (FFNs), bidirectional encoder representations from transformers (BERT), and generative pre-trained transformers (GPT) across 18 conditions in matching-to-sample (MTS) simulations. Conditions varied in training structure (linear series, one-to-many, and many-to-one), relation type (select-only, reject-only, and select-reject), and negative comparison selection (standard and biased). A probabilistic agent served as a benchmark, embodying purely associative learning. The primary goal was to determine whether artificial neural networks could demonstrate equivalence class formation or whether their performance reflected associative learning. Results showed that reject relations influenced agent performance. While some agents achieved high accuracy on equivalence tests, particularly with reject relations and biased negative comparisons, this performance was comparable to the probabilistic agent. These findings suggest that artificial neural networks, including transformer models, may rely on associative strategies rather than SE. This underscores the need for careful consideration of reject relations and more stringent criteria in computational models of equivalence.