策略转换的成本与顺序效应

灵活的策略转换是个体有效地解决问题的重要条件。策略转换需要成本已得到大量证明,但策略转换成本是否为对称转换成本尚无定论。基于已有研究,对策略转换中存在策略顺序困难效应与较差策略顺序调节效应两种典型的顺序效应进行了具体介绍。在此基础上提出了不对称策略转换成本可能是对称转换成本与策略顺序困难效应之和的假设,并进而提出设想:可通过操纵时间变量来分离策略顺序困难效应与较差策略顺序调节效应。此外,从策略转换成本的角度创新地阐释了策略选择的惰性与倒退现象。     

Further analysis of antecedent interventions on preschoolers' compliance

Functional analyses were conducted to identify reinforcers for noncompliance exhibited by 3 young children. Next, the effects of three antecedent-based interventions-noncontingent access to a preferred item, a warning, and a high-probability instructional sequence-were examined. The high-probability instructional sequence was effective for 1 child. Antecedent interventions were ineffective and extinction was necessary for the other 2 children.     

The computational complexity of scenario-based agent verification and design

We first advocate that the AUML (Agent Unified Modeling Language) notation, even in its new version, is not precise enough to adequately describe protocols. This problem was long identified by Harel and we propose to follow his solution: extend sequence diagrams with a “prechart”, i.e. single out the initiation sequence of the protocol. This new notation keeps readability and intuition, but is also technically adequate and is given a formal semantics. It actually is a form of simple temporal logics, equipped with a game-based semantics, which is appropriate for modeling agent-based systems. We then go on to study its complexity. Unsurprisingly, the version with protocol roles is undecidable. The main interesting problem is to synthesize agents that follow the protocol described. Surprisingly, it is undecidable even if we remove roles, alternatives, loops, asynchronous communication, conditions, constraints, negations (already removed in AUML). The complexity of checking whether a society of agents obeys a protocol given in this trivial notation is also surprisingly high: it is PSPACE-complete, like temporal logic, while we show that this simple language is strongly less expressive than temporal logic. Notations in-between have the expected increase in expressiveness, but no increase in complexity. This justifies the use of a language including alternatives, asynchronous communication and conditions, since it increases expressiveness with no cost in complexity.     

不同运动经历人群的内隐序列学习能力

考察不同运动经历人群的内隐序列学习能力。被试为上海体育学院小球运动员和非运动员;实验结合PDP,采用序列学习任务,并测试操作智商与记忆广度。结果发现,运动员在15个组段上的平均反应时、内隐学习量、自动提取贡献率上显著大于非运动员;不同水平运动员在内隐学习量上差异显著。研究结论:运动员的内隐序列学习能力显著好于非运动员,与运动水平有关,与智商无显著相关;这种内隐序列学习能力可能是某种运动能力的表现形式。     

时间序列关系推理研究概述

时间序列关系推理是对事件发生的先后顺序关系的推理,是日常生活思维的重要方面。已有的研究关注3类推理问题,探查了不同任务变式下成人时间序列关系推理过程和推理策略,研究结果多支持心理模型理论。未来的研究应探明3类问题的性质,从心理逻辑理论的角度深化策略的研究结果,进一步揭示推理的机制。     

Neural network processing of natural language: II. Towards a unified model of corticostriatal function in learning sentence comprehension and non-linguistic sequencing

A central issue in cognitive neuroscience today concerns how distributed neural networks in the brain that are used in language learning and processing can be involved in non-linguistic cognitive sequence learning. This issue is informed by a wealth of functional neurophysiology studies of sentence comprehension, along with a number of recent studies that examined the brain processes involved in learning non-linguistic sequences, or artificial grammar learning (AGL). The current research attempts to reconcile these data with several current neurophysiologically based models of sentence processing, through the specification of a neural network model whose architecture is constrained by the known cortico-striato-thalamo-cortical (CSTC) neuroanatomy of the human language system. The challenge is to develop simulation models that take into account constraints both from neuranatomical connectivity, and from functional imaging data, and that can actually learn and perform the same kind of language and artificial syntax tasks. In our proposed model, structural cues encoded in a recurrent cortical network in BA47 activate a CSTC circuit to modulate the flow of lexical semantic information from BA45 to an integrated representation of meaning at the sentence level in BA44/6. During language acquisition, corticostriatal plasticity is employed to allow closed class structure to drive thematic role assignment. From the AGL perspective, repetitive internal structure in the AGL strings is encoded in BA47, and activates the CSTC circuit to predict the next element in the sequence. Simulation results from Caplan's [Caplan, D., Baker, C., & Dehaut, F. (1985). Syntactic determinants of sentence comprehension in aphasia. Cognition, 21, 117-175] test of syntactic comprehension, and from Gomez and Schvaneveldts' [Gomez, R. L., & Schvaneveldt, R. W. (1994). What is learned from artificial grammars?. Transfer tests of simple association. Journal of Experimental Psychology: Learning, Memory and Cognition, 20, 396-410] artificial grammar learning experiments are presented. These results are discussed in the context of a brain architecture for learning grammatical structure for multiple natural languages, and non-linguistic sequences.     

A PILOT STUDY OF NATURALLY OCCURRING HIGH‐PROBABILITY REQUEST SEQUENCES IN HOSTAGE NEGOTIATIONS

In the current study, the audiotapes from three hostage‐taking situations were analyzed. Hostage negotiator requests to the hostage taker were characterized as either high or low probability. The results suggested that hostage‐taker compliance to a hostage negotiator's low‐probability request was more likely when a series of complied‐with high‐probability requests preceded the low‐probability request. However, two of the three hostage‐taking situations ended violently; therefore, the implications of the high‐probability request sequence for hostage‐taking situations should be assessed in future research.