Recent constraint-satisfaction models of explanation, analogy, and decision making claim that these processes are influenced by bidirectional constraints that promote coherence. College students were asked to reach a verdict in a complex legal case involving multiple conflicting arguments, including alternative analogies to the target case. Participants rated agreement with the individual arguments both in isolation before seeing the case, and again after reaching a verdict. Assessments of the individual arguments (including the competing analogies) shifted so as to cohere with their emerging verdict. Information about the character of the defendant in the initial case triggered a cascade of "spreading coherence", influencing decisions made about a subsequent case involving very different legal issues. Participants ' memory for their initial positions also shifted so as to cohere with their final positions. The coherence shifts were simulated by a constraint satisfaction model. The results demonstrate that an alogical process of constraint satisfaction can transform highly ambiguous inputs into coherent decisions. Bidirectional Reasoning 3 One of the most deep-rooted assumptions about human reasoning is that the flow of

How is information transmitted in a group? A multi-agent connectionist model is proposed that combines features of standard recurrent models to simulate the process of information uptake, integration and memorization within individual agents, with novel aspects that simulate the communication of beliefs and opinions between agents. A crucial aspect in belief updating based on information from other agents is the trust in the information provided, implemented as the consistency with the receiving agents’ existing beliefs. Trust leads to a selective propagation and thus filtering out of less reliable information, and implements Grice’s (1975) maxims of quality and quantity in communication. By studying these communicative aspects within the framework of standard models of information processing, the unique contribution of communicative mechanisms beyond intra-personal factors was explored in simulations of key phenomena involving persuasive communication and polarization, lexical acquisition, spreading of stereotypes and rumors, and a lack of sharing unique information in group decisions.

This article presents a neural network simulation of the out-group homogeneity effect (OHE). The model is a feedback network with delta-rule learning that has been previously used to simulate other aspects of stereotype learning, as well as causal learning and reasoning, and human memory. This simulation achieves 2 goals: First, we show that the model could successfully simulate the OHE. We argue that this is due to the error-correcting nature of delta-rule learning. Second, we show that each of 5 aspects of the simulation influences the size of the OHE: (a) the ratio of in-group to out-group size, (b) the overall population size, (c) the learning rate, (d) the decay rate for weights, and (e) increased learning for extreme cases. The psychological relevance of these parameters and ways to study them are presented. Advantages of the model in terms of breadth of coverage for studying social cognitive phenomena are discussed. The tendency to perceive out-group members as relatively similar to one another and in-group members as relatively more heterogeneous or dissimilar is known as the out-group homogeneity effect (OHE). This tendency to perceive out-group members as “all the same ” is argued to increase stereotyping (Judd,

Recent theorizing about the nature of the cognitive impairment in autism suggests that autistic individuals display abnormally weak central coherence, the capacity to integrate information in order to make sense of ones environment. Our article shows the relevance of computational models of coherence to the understanding of weak central coherence. Using a theory of coherence as constraint satisfaction, we show how weak coherence can be simulated in a connectionist network that has unusually high inhibition compared to excitation. This connectionist model simulates autistic behavior on both the false belief task and the homograph task.

Abstract: Research methods are "technique(s) for... gathering data " (HARDING 1986) and are generally dichotomised into being either quantitative or qualitative. It has been argued that methodology has been gendered (OAKLEY 1997; 1998), with quantitative methods traditionally being associated with words such as positivism, scientific, objectivity, statistics and masculinity. In contrast, qualitative methods have generally been associated with interpretivism, non-scientific, subjectivity and femininity. These associations have led some feminist researchers to criticise (REINHARZ 1979; GRAHAM 1983; PUGH 1990) or even reject (GRAHAM & RAWLINGS 1980) the quantitative approach, arguing that it is in direct conflict with the aims of feminist research (GRAHAM 1983; MIES 1983). It has been argued that qualitative methods are more appropriate for feminist research by allowing subjective knowledge (DEPNER 1981; DUELLI KLEIN 1983), and a more equal relationship between the researcher and the researched (OAKLEY 1974; JAYARATNE 1983; STANLEY & WISE 1990). This paper considers the quantitative/qualitative divide and the epistemological reasoning behind the debate before investigating two research methods, the statistical survey and the semi-structured interview, in respect of their use to feminist researchers. It concludes by arguing that different feminist issues need different research methods, and that as long as they are applied from a feminist perspective

This paper represents an attempt to summarize what is known in cognitive, developmental and social psychology on the nature of human naive theories, The parallel human mind / www is drawn, and it is shown how the challenges addressed in Data Mining and Knowledge Acquisition are present in the mind of the individual as well. The process of cognitive development and knowledge acquisition is such that uncoordinated must result. There is no process active in Long-Term memory to harmonize inconsistent parts. Coordination takes place in Working Memory (WM), and cognitive psychology has long established its extreme smallness. Units of explanation and domains of coherence are therefore small. This is, indeed, a limitation of our cognition, but it is tenable pragmatically. Naive theories on any one issue do not form, psychologically, cognitively, a natural kind.

A multi-agent connectionist model is proposed that consists of a collection of individual recurrent networks that communicate with each other, and as such is a network of networks. The individual recurrent networks simulate the process of information uptake, integration and memorization within individual agents, while the communication of beliefs and opinions between agents is propagated along connections between the individual networks. A crucial aspect in belief updating based on information from other agents is the trust in the information provided. In the model, trust is determined by the consistency with the receiving agents ’ existing beliefs, and results in changes of the connections between individual networks, called trust weights. Thus activation spreading and weight change between individual networks is analogous to standard connectionist processes, although trust weights take a specific function. Specifically, they lead to a selective propagation and thus filtering out of less reliable information, and they implement Grice’s (1975) maxims of quality and quantity in communication. The unique contribution of communicative mechanisms beyond intra-personal processing of individual networks was explored in