Mental ability and common sense in an artificial society

Abstract

How we decide what is right or wrongWe read newspapers and watch TV every day. There are many issues and many controversies. Since media are free, we can hear arguments from every possible side. How do we decide what is wrong or right? The first condition to accept a message is to understand it; messages that are too sophisticated are ignored. So it seems reasonable to assume that our understanding depends on our ability and our current knowledge. Here we show that the consequences of this statement are surprising and funny. How do we learn?To demonstrate this, we propose a computational model with two assumptions [1]. The first is that messages can be represented as points on a plane of a finite area, say, a square a×a. Consequently, we can measure the distance between messages. The second assumption is that we can understand a message if it is not too far from what we already know.As a direct consequence of these two assumptions, we obtain a simple model of learning. In this model the mind is represented by an area around the messages understood by the mind's owner. Her/his ability is represented by a critical distance D c . A new message can be grasped if its distance to the closest previously understood message is shorter than D c . If this distance is longer, the message is ignored.Let us consider a new area of experience: differential calculus, traffic regulations, stock market, foreign policy or classic Latin grammar can serve MENTAL ABILITY AND COMMON SENSE IN AN ARTIFICIAL SOCIETYHaving equally valid premises pro and contra, what does a rational human being prefer? The answer is: nothing. We designed a test of this kind and applied it to an artificial society, characterized by a given level of mental ability. A stream of messages from media is supplemented by ongoing interpersonal communication. The result is that high ability leads to wellbalanced opinions, while low ability produces extreme opinions.

Searching for Effective and Efficient Way of Knowledge Transfer within an Organization

“…The starting point for our research is recently proposed a CA model (Kowalska-Styczeń et al, 2017), in which-basing on empirical findings (Reagans and McEvily, 2003)-a small distance of common knowledge between the source and recipient was assumed. Such approach is consistent with Deffuant et al model (Deffuant et al, 2000) of opinion dynamics where opinion exchange among agents is possible only when sender and recipient have similar opinions (Hegselmann and Krause, 2002;Malarz, 2006;Kułakowski, 2009;Malarz et al, 2011;Malarz and Kułakowski, 2014).…”

Influence of a Range of Interaction among Agents on Efficiency and Effectiveness of Knowledge Transfer within an Organisation

“…Such approach is not different from Deffuant et al [17] model of opinion dynamics, where opinion exchange among agents is possible only when sender and recipient have similar opinions [18][19][20][21][22] and consistent with empirical findings regarding knowledge transfer in organisation [8]. Also simulations driven by the homophily principle assume that 'agents are likely to exhibit strong preferences towards agents with which they are similar' [23].…”

Model of Knowledge Transfer Within an Organisation

“…The model simplification introduce blocking the transfer of knowledge between agents (the leader and follower) if a distance of their knowledge (measured by the difference in the number of chunks of knowledge) is larger than one. This approach is not much different from the opinion exchange model of Deffuant et al [2000] when interaction among agents is possible only when the distance between agents opinions in one- [Hegselmann and Krause, 2002, Malarz, 2006, Zhao et al, 2016, Dong et al, 2016 or two-dimensional [Kułakowski, 2009, Malarz and Kułakowski, 2014, Malarz et al, 2011 space of opinions is smaller than assumed confidence level.…”