IR generally distinguishes between three levels of analysis: the system, the state, and the individual – but the group level is also important to consider as a fourth. To be able to use the level of analysis as an analytical device, we need to be clear about what we are most interested in.

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The computational level of analysis describes both what problem is being solved by the information processing system, and why the problem is being solved. In other words, the computational level is simply a description of the input-output behaviour of a particular system.

Marr’s “tri-level hypothesis” (Dawson, 1998), that information-processing systems can be analyzed in terms of the problems that they solve (Marr’s computational level), the representations and processes by which they solve them (the algorithmic and representational level), and the physical instantiation of these …

The three levels correspond roughly to: (i) defining the problem and setting out how, in principle, it can be solved; (ii) designing a detailed simulation of the process; and (iii) building a working system that will carry it out (see Box 1).

Tri-Level Hypothesis 19-20). Marr has defined these levels as computational, algorithmic, and implementational. The computational level is a description of what information processing problem is being solved by the system. The algorithmic level is a description of what steps are being carried out to solve the problem.

Why does Marr maintain that explanation is top-down? There are many different ways of implementing a given algorithm. Many different algorithms can in principle compute the same task. SHRDLU’s systems are divided into groups according to the specific job they carry out.

Subtle point: Marr considered representation to be a key element for understanding computation, but at the same level as algorithm. More fine-grained is the implementation level: how the information-processing model is solved biologically by cells, synapses, neuronal circuits, etc.

The computational theory of mind holds that the mind is a computational system that is realized (i.e. physically implemented) by neural activity in the brain. The computational theory of mind is related to the representational theory of mind in that they both require that mental states are representations.

Implementation Level – Communication. The ability to send and received SNOMED CT expressions in messages or other communication is partially dependent on data entry, storage and retrieval capabilities.

The theory of computation is a branch of computer science and mathematics combined that “deals with how efficiently problems can be solved on a model of computation, using an algorithm”. It studies the general properties of computation which in turn, helps us increase the efficiency at which computers solve problems.

The essence of the theory of computation is to help develop mathematical and logical models that run efficiently and to the point of halting. Since all machines that implement logic apply TOC, studying TOC gives learners an insight into computer hardware and software limitations.

The computational metaphor—the comparison of the mind/brain to the program/computer and the program/computer to the mind/brain—is now the dominant intellectual tool of many of the behavioral sciences.

No, the human brain is definitely not a Turing machine, a Turing machine is an abstraction of a very specific form of computation with a tape and a moving head reading and writing symbols, this is definitely not the way in which the brain is or works.

According to CTM, cognitive states are constituted by computational relations to mental representations of various kinds, and cognitive processes are sequences of such states. CTM develops RTM by attempting to explain all psychological states and processes in terms of mental representation.

Neurons and the processes they support – including consciousness – are the same thing. In a computer, software and hardware are separate; however, our brains and our minds consist of what can best be described as wetware, in which what is happening and where it is happening are completely intertwined.

Both of them have memory, both of them use electrical signals, both of them can retrieve and transmit data, both of them have partitions and both of them connect data in order to reach to conclusions which are logical and working.

The brain is a biological organ, and not a digital computer. Neuroscience has discovered that while the brain mediates between the body and the environment, it does not command the body. Often brain problems can be traced to problems in the rest of the body, and not to a malfunctioning brain.

Both use electrical signals to send messages. The brain uses chemicals to transmit information; the computer uses electricity. Even though electrical signals travel at high speeds in the nervous system, they travel even faster through the wires in a computer. Both transmit information.