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Machine Learning – Principles and Algorithms
Published in Rashmi Priyadarshini, R M Mehra, Amit Sehgal, Prabhu Jyot Singh, Artificial Intelligence, 2023
Gagandeep Kaur, Satish Saini, Amit Sehgal
The human brain prepares an internal model of the world around us based on the information perceived by the senses. This model, along with knowledge about the past, is used to take actions for the current state and also make predictions about the future. Similarly, in RL, the agent develops a world model and utilizes the representation of past and present knowledge for predictive modeling. The observations from the environment are processed by the World Model in two stages. The Vision Model encodes these observations from a high dimensional data into a low dimensional latent vector. This information is processed with the historic codes present in the memory stage, which is implemented using some form of neural network, to create a predictive representation capable of predicting future states. Representations from the Vision Model and Memory are compared by the controller to select the optimal or most suitable action.
Bidirectional Neural Interfaces
Published in Chang S. Nam, Anton Nijholt, Fabien Lotte, Brain–Computer Interfaces Handbook, 2018
Mikhail A. Lebedev, Alexei Ossadtchi
Going beyond reflexes and voluntary movements, some developers of robots (Hoffmann et al. 2010), prostheses (Pazzaglia & Molinari 2016), and NIs (Alimardani et al. 2016; Lebedev & Nicolelis 2006) build their ideas around the concept of body schema. This concept was proposed by Head and Holmes (1911) as an explanation of how the brain integrates multiple streams of information from peripheral sensors to form a coherent model of the body (Maravita & Iriki 2004; Maravita et al. 2003). The internal model theory (Kawato 1999; Wolpert et al. 1995) is a modern version of the body schema theoretical framework. The internal model theory delineates two components: the controlled object (e.g., a body part) and the neural controller. To optimize the performance, the controller builds an internal model that describes the properties of the object. When planning a movement, the controller utilizes the internal model to form an expectation of how the body part would move. Next, during motor execution, afferent information from the body part is compared with the expectation, and a correcting command is issued if the incoming sensory information is different from the expected state. It has been proposed that NI should utilize an internal model to perform better (Cui 2016; Golub et al. 2012). Similar optimization ideas can be found in the theory of optimal feedback control (Todorov 2004; Todorov & Jordan 2002) that was recently applied to NI design (Benyamini & Zacksenhouse 2015; Shanechi et al. 2016).
Conceptual Frameworks for Interpreting Motor Cortical Function: New Insights from a Planar Multiple-Joint Paradigm
Published in Alexa Riehle, Eilon Vaadia, Motor Cortex in Voluntary Movements, 2004
FIGURE 6.1 Two alternate frameworks for interpreting how the brain performs visually guided movements. (A) The notion of sensorimotor transformations assumes that information on spatial targets is converted into muscle activation patterns through a series of intermediary representations. This framework leads to the scientific problem of identifying how these representations are reflected in the discharge pattern of neurons in different brain regions. (B) The idea of internal models is that neural processes mimic the properties of the muscu- loskeletal system and physical objects in the environment. This framework leads to the scientific problem of identifying how information related to the motor periphery and physical loads is reflected in the discharge pattern of neurons.
Utilization of cues in action anticipation in table tennis players
Published in Journal of Sports Sciences, 2018
Qi Zhao, Yingzhi Lu, Kyle J. Jaquess, Chenglin Zhou
As expected, both regional players and college players were more accurate than novices in anticipating the outcome of table tennis serves based on kinematic information. This result is consistent with previous sport-specific anticipation studies. While superior anticipation has been reported by skilled athletes, such as tennis players (Shim, Carlton, & Kwon, 2006), cricket players (Müller et al., 2006), over novices based on advanced cues in temporal occlusion test, the current study offered further information about using kinematic information by experienced athletes with the use of full-video. Several studies have shown that the anticipatory internal model, which is established due to increased motor expertise, creates an representation of probable outcomes for observed actions (Ramnani & Miall, 2004; Verfaillie & Daems, 2002). As such, full kinematic information was offered in the present study, indicating that the ability to anticipate the outcome of a motor sequence is dependent upon motor expertise, rather than the completeness of the kinematic information.
Operational learning with sensory feedback for controlling a robotic thumb using the posterior auricular muscle
Published in Advanced Robotics, 2019
Tadayoshi Aoyama, Hiroshi Shikida, Rubens Schatz, Yasuhisa Hasegawa
Humans can intuitively control and predict the motions of tools using their hands. This is possible because humans possess an internal model of the tool in their cerebellum [13]. Internal models are dynamic representations of bodies or tools, which can be classified into inverse and forward models (Figure 1). The inverse model represents the controller shown in Figure 1, and determines the appropriate motor command based on the difference between the desired state and initial states. The forward internal model predicts motion based on the efference copy of the motor command.
Occupant–vehicle dynamics and the role of the internal model
Published in Vehicle System Dynamics, 2018
The primary aim of the paper is to outline the role of the internal model hypothesis in understanding and modelling occupant–vehicle dynamics. The internal model hypothesis asserts that a human learns a mental model of their environment and uses this model in perception, cognition and action processes. The internal model hypothesis is widely adopted in the field of neuroscience [5] and is well supported by behavioural studies. The hypothesis is amenable to mathematical representation.