5. Perception5.1. Sensation versus

5. Perception

5.1. Sensation versus perception
Psychologists and philosophers have often distinguished between sensation and perception. The distinction is not easy to define rigorously, but the general idea is clear enough. Sensation is raw sensory input, while perception is a representation of how things are in the environment based upon, or suggested by, this input. So, for example, when looking at a wire-frame cube, the sensory input consists of twelve co-planar line segments: four horizontal, four vertical, and four diagonal, arranged in the familiar way. What one perceives is a cube, a three-dimensional object in space. That the perception is an interpretation of the sensory input is highlighted by the fact that one can, at least in some cases, switch which face of the cube is in front, as with the Necker cube. Here there are two different interpretations that can be placed on the same sensory input; two different perceptual states based on the same sensory state.
The sorts of representational states that result from perception are extremely complex, but for purposes of the present discussion I will focus on what I take to be the core aspects. Through perception we become aware of objects in our surroundings. A bit more specifically, we become aware of some number of objects and surfaces, their rough sizes and shapes, their dynamical properties (especially movements), and their egocentric locations. To have some handy terminology, I will refer to this as an environment emulator. Clearly one of the primary functions of perception is the formation of an accurate estimate of the environment, and this will be embodied in the environment emulator.
Look again at Figure 7. In section 4, I highlighted one aspect of this diagram – its combination of modal and amodal emulators. But now I want to draw attention to another aspect, which is that the feedback from the emulator to the controller does not go through the measurement process. In Figure 2, the control context within which we started involved a controller that was given a goal state, and got feedback that was used to assess the success of the motor program in achieving that goal state. In the feedback control scheme, the feedback is necessarily whatever signal is produced by the plant’s sensors, and this imposes a requirement that the goal specification given to the controller be in the same format as the feedback, for only if this is the case can an assessment between the desired and actual state of the plant be made. That is, the goal state specification had to be in sensory terms.
In the pseudo-closed-loop scheme of Figure 4, and the KF-control scheme of Figure 6, the idea that the feedback sent from the emulator to the controller was also in this “sensory” format was retained. In the latter case this was made explicit by including a “measurement” of the emulator’s state parallel to the measurement of the real process in order to produce a signal in the same format as the real signal from the plant.
But retaining this “measurement” is neither necessary nor, in many cases, desirable. The real process/plant has many state variables, only a small sampling of which are actually measured. In the biological case, access to the body’s and environment’s states through sensation is limited by the contingencies of the physiology of the sensors. A system with an amodal emulator that is maintaining an optimal estimate of all the body’s or environment’s relevant states is needlessly throwing away a great deal of information by us- ing only the mock “sensory” signal that can be had by subjecting this emulator to a modality-specific measurement. There is no need to do this. The emulator is a neural system: any and all of its relevant states can be directly tapped.13 This is the meaning of the fact that in Figure 7 the feedback to the controller comes directly from the emulator, without the modality-specific “measurement” being made.
The practical difference between the two cases is significant, because, as already mentioned, a modality-specific measurement process might very well throw out a great deal of useful information. But the conceptual difference is more important for present purposes. It is not inaccurate to describe the “measured” or “modal” control schemes, including the KF-control scheme of Figure 6, as systems that control sensation. Their goal is a sensory goal, they want their sensory input to be like thus-and-so, and they send out control signals that manage to alter their sensory input until it is like thus-and-so. The information they are getting is exclusively information about the state of the sensors. But in the unmeasured amodal variant, the controller has its goal specified in terms of objects and states in the environment, and the feedback it gets is information about the objects in its egocentric environment.
The less sophisticated systems are engaged with their sensors. This

Kết quả (Việt) 1:

5. nhận thức5.1. cảm giác so với nhận thứcNhà tâm lý học và triết gia thường phân biệt giữa cảm giác và nhận thức. Sự khác biệt không phải là dễ dàng để xác định một cach nghiêm tuc, nhưng những ý tưởng chung là đủ rõ ràng. Cảm giác là cảm giác đầu vào nguyên liệu, trong khi nhận thức là một đại diện làm việc trong môi trường dựa trên, hoặc đề xuất bởi, đầu vào này. Vì vậy, ví dụ, khi nhìn vào một khối khung dây, cảm giác đầu vào bao gồm mười hai đoạn đường phẳng co: bốn ngang, 4 theo chiều dọc, và bốn chéo, sắp xếp cách quen thuộc. Những gì một cảm nhận là một khối lập phương, một đối tượng ba chiều trong không gian. Nhận thức là một giải thích về cảm giác đầu vào được tô đậm bởi một thực tế là một trong những có thể, ít trong một số trường hợp, chuyển đổi mặt của khối lập phương là ở phía trước, như với Necker khối lập phương. Ở đây có hai cách diễn giải khác nhau có thể được đặt trên cùng một cảm giác đầu vào; hai perceptual tiểu bang khác nhau dựa trên cùng một trạng thái cảm giác.Các loại kỳ representational là kết quả của nhận thức là cực kỳ phức tạp, nhưng cho các mục đích của cuộc thảo luận hiện nay, tôi sẽ tập trung vào những gì tôi có là những khía cạnh cốt lõi. Thông qua nhận thức chúng ta trở thành nhận thức của các đối tượng trong môi trường xung quanh của chúng tôi. Cụ thể hơn một chút, chúng ta trở thành nhận thức của một số đối tượng và bề mặt, kích thước thô và hình dạng, tính động lực của họ (đặc biệt là phong trào) và vị trí của họ egocentric. Có một số thuật ngữ hữu ích, tôi sẽ tham khảo này như là một trình giả lập môi trường. Rõ ràng là một trong các chức năng chính của nhận thức là sự hình thành của một ước tính chính xác của môi trường, và điều này sẽ được thể hiện trong các mô phỏng môi trường.Look again at Figure 7. In section 4, I highlighted one aspect of this diagram – its combination of modal and amodal emulators. But now I want to draw attention to another aspect, which is that the feedback from the emulator to the controller does not go through the measurement process. In Figure 2, the control context within which we started involved a controller that was given a goal state, and got feedback that was used to assess the success of the motor program in achieving that goal state. In the feedback control scheme, the feedback is necessarily whatever signal is produced by the plant’s sensors, and this imposes a requirement that the goal specification given to the controller be in the same format as the feedback, for only if this is the case can an assessment between the desired and actual state of the plant be made. That is, the goal state specification had to be in sensory terms.In the pseudo-closed-loop scheme of Figure 4, and the KF-control scheme of Figure 6, the idea that the feedback sent from the emulator to the controller was also in this “sensory” format was retained. In the latter case this was made explicit by including a “measurement” of the emulator’s state parallel to the measurement of the real process in order to produce a signal in the same format as the real signal from the plant.But retaining this “measurement” is neither necessary nor, in many cases, desirable. The real process/plant has many state variables, only a small sampling of which are actually measured. In the biological case, access to the body’s and environment’s states through sensation is limited by the contingencies of the physiology of the sensors. A system with an amodal emulator that is maintaining an optimal estimate of all the body’s or environment’s relevant states is needlessly throwing away a great deal of information by us- ing only the mock “sensory” signal that can be had by subjecting this emulator to a modality-specific measurement. There is no need to do this. The emulator is a neural system: any and all of its relevant states can be directly tapped.13 This is the meaning of the fact that in Figure 7 the feedback to the controller comes directly from the emulator, without the modality-specific “measurement” being made.The practical difference between the two cases is significant, because, as already mentioned, a modality-specific measurement process might very well throw out a great deal of useful information. But the conceptual difference is more important for present purposes. It is not inaccurate to describe the “measured” or “modal” control schemes, including the KF-control scheme of Figure 6, as systems that control sensation. Their goal is a sensory goal, they want their sensory input to be like thus-and-so, and they send out control signals that manage to alter their sensory input until it is like thus-and-so. The information they are getting is exclusively information about the state of the sensors. But in the unmeasured amodal variant, the controller has its goal specified in terms of objects and states in the environment, and the feedback it gets is information about the objects in its egocentric environment.The less sophisticated systems are engaged with their sensors. This