Definition of the Subject
Cognitive Robotics is an emerging field ofrobotics , which will continue to evolve for the years to come. The field of cognitive robotics generallycomprises the design and use of robots with human-like intelligence in perception, motor control and high-level cognition. To realize cognitive robotsmany overlapping disciplines are needed, e. g. robotics, artificial intelligence, cognitive science, neuroscience, biology, philosophy, psychology,and cybernetics. Thus attempting to tightly define the subject is not constructive as often its nature is amorphous, growing and a strict definitioncould exclude future relevant work.
Work by Clark and Grush [1] towards a cognitive robotdefinition is well respected. We quote some importantconsiderations below:
We hold that fluent, coupled real-world action‐taking is a necessary component of cognition.
Cognition, we want to say, requires both fluent real-world coupling and the capacity to improve such engagements by the use...
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- Amygdala:
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Amygdala consists of almond‐shaped groups of neurons located within the limbic lobe in the brain. The amygdale performs primary roles in the formation and storage of memories associated with emotions and is said to have a substantial role in mental states.
- Basal ganglia:
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Basal Ganglia are a collection of subcortical neuronal group and have a significant role in the control of movement.
- Central executive agent (CEA):
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CEA is a cognitive or compound agent responsible for high-level executive control, such as reasoning, task switching and realization of internal rehearsal, e. g. within the ISAC cognitive architecture.
- Chinese room argument:
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John Searle developed a thought experiment called the “Chinese Room” argument against what he calls “strong AI”. Searle describes a scenario in which a person who knows no Chinese is locked in a room full of boxes of Chinese symbols together with a book of instructions for manipulating symbols. This person receives questions in Chinese from under the door. If the person in the room is able to pass out Chinese symbols using the instruction book to produce correct answers to the questions, he passed the Turing Test for intelligence in Chinese, but he does not understand a word of Chinese.
- Connectionist models :
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Connectionist models of cognition are structured on the concept of neural networks. Connectionist networks provide an account for the complex behavior in a way parallel distributed processing (PDP) does. There is no way to distinguish between simple and complex representations in connectionist models. In this sense, they are considered to be sub‐symbolic.
- Cortex:
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Cortex (or cerebral cortex) is a surface structure in the brain responsible for many brain functions including attention, sensory processing, motor functions, awareness, language processing and arguably consciousness. The human cortex is 2–4 mm thick and consists of large sheets of mostly layered neurons.
- First-order cybernetics:
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First-order cybernetics considers control and communication in the animal and machine, where the agent receives feedback, including utility of its actions, from the environment.
- Cartesian theater :
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A centered locus in the brain called Cartesian materialism, because it is the view one arrives at when one discards Descartes' dualism, but fails to discard the associated imagery of a central (but material) theater where it all comes together.
- Global workspace :
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Multiple parallel specialist processes compete and co‐operate for access to a global workspace. If granted access to the global workspace, the information a process has to offer is broadcast back to the entire set of specialists.
- Humanoid robots :
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There is no universally accepted definition for a humanoid robot today. However, it is widely accepted that a humanoid robot must have a body somewhat resembled to a human body, exhibit human-like behavior, and be able to interact with humans using human-level intelligence. As of today, no existing humanoid robots satisfy all these requirements.
- ISAC :
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ISAC stands for Intelligent Soft Arm Control. The name arises from the fact that the arm is highly compliant and safe for working with and around people. In its multiagent architecture called the Intelligent Machine Architecture (IMA), human and many modules within the humanoid are represented as distinct agents within a common computational framework.
- Minimum robust representationalism (MRR):
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MRR is a notion, rather than a formal definition, put forward by Clark and Grush that addresses the problem of internal representation when addressing cognitive phenomena. The emphasis on emulators differs from the classical ideas of cognitivism and representationalism. Transparent (i. e. analytically traceable) emulator circuitry is the minimal needed to usefully consider representations of external states.
- Multiagent systems (MAS) :
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A multiagent system (MAS) is a software system composed of multiple agents and collectively capable of reaching goals that are difficult to achieve by an individual agent. An agent within MAS can be autonomous in the sense that it has own decision‐making capability or non‐autonomous like a simple input‐output device. MAS agents can include human agents like the case study in this section.
- Neural networks :
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Neural networks, or artificial neural networks , are a class of networks of simple processing units which can exhibit complex behavior. They were inspired by the way biological nerve systems, such as the brain, process information. Simple neural networks consist of three layers, input, hidden and output.
- Production systems :
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Production systems are symbolic artificial intelligence systems, i. e. they manipulate symbols, instead of numbers. Production systems are composed three parts: a global database, production rules and a control structure. Production rules (or productions) are called if-then rules.
- Second‐order cybernetics :
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Second‐order cybernetics recognizes that the agent has an important effect back on the environment and the two systems affect each other.
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Kawamura, K., Browne, W. (2009). Cognitive Robotics. In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, New York, NY. https://doi.org/10.1007/978-0-387-30440-3_74
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