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Top2. System Thinking And Semiotic Knowledge Representation
Cognitive and computer sciences have accumulated multiple models of intelligent processes. It would be possibly wrong to say that brain plays such models. But the right statement is that those models reflect some brain processes. Assume that we need to design a system, where human mind is a prototype. To start building, we need to provide its specifications that are based on some rationale. This is needed for Use Cases that describe how system may work. It would be also smart to reuse what is already accumulated in other areas. And if we try to apply experience that has been accumulated in cognitive and computer sciences and software and computer industries, we shall notice some interesting analogies.
Virtual reality and modern computer games become more and more sophisticated, and closer to real life. We are trying to build more and more sophisticated game engines. But it would be no mistake to state a trivial on the first sight thing: life is also a game. Could our brain use same principles that a sophisticated intelligent game engine would be using? The life game engine needs to drive a core life cycle that consists of perception, cognition, prediction, decision, and action. (Figure 1) This process is not completely linear, and there are sub-cycles, and feedbacks. Cognition builds situation model for the prediction process from perceptual information and other cognitive models, which also include linguistic models with help of Synthesis – Analysis cycle. Third component of this cycle – Search – is not shown.
Figure 1. Cycles of intelligent engine. Please note that a separation between perception and cognition is imaginary and in fact they form a single multilevel hierarchical system with feedbacks. In this sense, they are perceptual and conceptual levels in the hierarchy with multiple feedbacks between levels rather than separated subsystems. Also, prediction and emotions are shown only between cognition and actions while they form feedback mechanisms on every level.
Outcomes of prediction process transform via Goals into Decision. Emotional components (Kuvich, 2005; Perlovsky, Deming, & Ilin, 2011) play role of positive or negative feedbacks to generate a Decision upon the cognitive models. Language models are inseparable part of the cognitive models, and they are shown here as such. Decision turns appropriate Action on, and cycle repeats.