# A Review of Cognitive Control: Advancement, Definition, Framework, and Prospect
## 2 Cognitive Control Research Overview
### Cognitive Control Based on CDS  
CDS is also an engineering system that is inspired by human cognition. Research on CDS originates from cognitive radar [102] and cognitive radio [103] and is then extended to the automatic control field [12]. Research on CDS was carried out by [PERSON]; its concept was first proposed in [104]. In [12], the basic principles of CDS were explained in detail, and cognitive radar and cognitive radio were reconsidered from the perspective of CDS; that is, cognitive radar is an application that mimics the human brain, whereas cognitive radio is an application motivated by human cognition. More importantly, cognitive control based on CDS was proposed as the first special function of CDS, which is a control method that incorporates the state-space model and entropic state model. \begin{table}
\begin{tabular}{c l l} \hline \hline  & **Research Content** & **References** \\ \hline
1. & Three-layer cognitive robot architecture & [72; 74; 75; 76; 77; 78] \\
2. & ISAC cognitive robot & [80; 81; 83; 84; 85] \\
3. & SAS for cognitive robots & [86; 87; 88; 89; 90; 91; 92] \\
4. & CRAM cognitive robot architecture & [93; 94; 95; 96; 97; 98; 99; 100; 101] \\
5. & Other cognitive robot architectures & [68; 70; 71; 69; 88; 71] \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Cognitive control in robotics. Figure 14: A schematic representation of the CRAM cognitive architecture [94]. Cognitive control based on CDS is established on the information gap. [PERSON] believes that since information is critical for control systems, a satisfactory level of control performance could be achieved, and the risk involved is reduced by properly defining the task-specific information gap and decreasing it during the control process. Specifically, available information is the information extracted from noisy measurements; regarding the task at hand, available information can be partitioned into relevant information and redundant information; sufficient information is defined as the required information for performing the task at hand with minimal risk; finally, the information gap is defined as the difference between sufficient information and relevant information [105]. The definition of risk presented in [106] is referenced by [PERSON], i.e., the sufficiency of a statistic for a particular task is specified by the risk associated with a control or decision policy. In statistical decision theory, risk is usually defined as the expected loss. In this subsection, cognitive control is described within the context of CDS. To simplify the description, cognitive control based on CDS is referred to as cognitive control for short, under the condition that there is no ambiguity. The architecture of the cognitive control system is shown in Figure 15[105]. The perceptual part and the executive part are connected to form a closed loop called PAC. In each PAC, the sensory measurements from the physical system and environment are processed by an estimation algorithm (such as a Bayesian filter) in the perceptual part to extract the relevant information. Then, the entropic state is calculated by the entropic information processor and sent to the executive part through the feedback channel. The entropic state is the quantification of the information gap, and its calculation method is determined by the specific tasks. A group of potential cognitive actions is selected from the actions space by the planner according to the current entropic state, which is evaluated by the cognitive controller through the shunt cycle, and the predicted entropic state of each cognitive action is obtained. The cognitive action to be executed is selected by policy from this group of cognitive actions according to the maximum Bayesian posterior and applied to the physical system or environment to reduce the entropic state of the system in the next PAC.