Design of Cognitive Machines

Author(s):  
Farley Simon Nobre ◽  
Andrew M. Tobias ◽  
David S. Walker

This chapter is concerned with the design of cognitive machines. These machines and their models were chosen in order to increase and to improve: i. The degree of cognition of the organization, ii. the capability of the organization for information processing and management, and iii. the ability of the organization to make decisions. Therefore Chapter VI introduces the design of cognitive machines with capabilities to carry out complex cognitive tasks in organizations - and in particular the task of decision-making which involves representation and organization of knowledge via concept identification and categorization along with the manipulation of perceptions (or percepts)1, concepts2, and mental models3. The ability of these machines to manipulate a percept provides them with higher levels of information-processing than other symbolic-processing machines4; and according to the theory of levels of processing in cognition (Reed, 1988), these machines can mimic (even through simple models) cognitive processes of humans (Nobre, 2005). Percepts and thus concepts5 (along with mental models) are described by words, propositions and sentences of natural language (Zadeh, 2001).

Cognitive biases can be produced by the constraints of information processing, as has been widely studied using different cognitive tasks both in clinical and healthy populations. Furthermore, these biases have been found in different areas of society (legal, economic, education, etc.) whose impact on the decision-making process is important. Often these biases help us make quick and appropriate decisions, but other times they lead to erroneous decisions. Within the cognitive biases due to inadequate processing of information, there are three main groups: perceptional bias, attentional bias, and memory bias. This chapter explains these three groups of cognitive biases. Subsequently, it offers a detailed explanation of some of the cognitive biases that have been studied in the fields of cognitive psychology. Finally, the author creates an alphabetical list of these biases and brief definitions.


Author(s):  
Vladimir A. Maksimenko ◽  
Alexander Kuc ◽  
Nikita S. Frolov ◽  
Marina V. Khramova ◽  
Alexander N. Pisarchik ◽  
...  

Author(s):  
Michael P. Clamann ◽  
Melanie C. Wright ◽  
David B. Kaber

Limitations in automation (expert system) capabilities and negative human performance consequences of automation in complex systems have led to the contention that use of computer assistance in high-level human-machine system information processing may be inappropriate. Adaptive automation (AA) has been explored as a solution to these problems; however, research has focused on the performance effects of dynamic control allocations of early sensory and information acquisition functions between human operators and computer controllers of complex systems. It has examined to a limited extent the human performance and workload effects of AA of cognitive tasks, such as decision-making, or of psychomotor functions such as response execution. This research compared the affects of AA applied to psychomotor tasks and cognitive tasks, including information monitoring, information analysis, decision-making, and action implementation, on overall human-machine system performance. Results demonstrated that operators are better able to adapt to AA when applied to lower level functions, such as information acquisition and action implementation, as compared to AA of information analysis and decision making tasks. The results also provided support for the use of AA, as compared to completely manual control.


1993 ◽  
Vol 18 (1) ◽  
pp. 48-62 ◽  
Author(s):  
Gershon Tenenbaum ◽  
Raya Yuval ◽  
Gabi Elbaz ◽  
Michael Bar-Eli ◽  
Robert Weinberg

Team handball players (N = 118) underwent a number of cognitive tests to examine how much of their decision making (DM) ability, as measured through responses to game slides projected to them for 2 seconds under low and high exertion levels (i.e., walking and running), was accounted for by cognitive components. A stepwise multiple linear regression indicated that experience was the most pronounced predictor of DM capacity in both exertion conditions. In the walking condition, concentrational consistency, avoidance of concentrational mistakes, and short-term memory, together with experience, produced a multiple R of 0.48 with decision making. In the running condition, choice reaction time (CRT), intelligence, and short-term memory, together with experience, correlated 0.46 with DM. These differences in cognitive abilities, as predictors of DM under walking and running conditions, are discussed in terms of information processing models and other cognitive processes. Key words: cognition, decision making, information processing


2018 ◽  
Vol 41 ◽  
Author(s):  
Kevin Arceneaux

AbstractIntuitions guide decision-making, and looking to the evolutionary history of humans illuminates why some behavioral responses are more intuitive than others. Yet a place remains for cognitive processes to second-guess intuitive responses – that is, to be reflective – and individual differences abound in automatic, intuitive processing as well.


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