Preface

Natural cognition systems, such as those of animals, humans, and many in nature, inspire the development of cognitive robots, which is an emerging interdisciplinary field in robotics. These robots represent forms of embodied cognition that focus on predictive capabilities, anticipate intended actions by perceiving their operational environments, and determine the necessary decisions and motor control. The cognitive robotics field describes robots that are continuously evolving and can achieve their goals by perceiving and interacting with their natural environment, recognizing and understanding events of interest, conducting adaptable planning, and anticipating the outcome of their actions and the actions of other entities sharing the same environment. These interactions enable the development of cognition capabilities through effective sensory-motor coordination. These robots use learning dynamics to exploit the full power of these interactions to deal with environment and task uncertainty and engage in continuous real-time reasoning.

This book provides up-to-date research development in the field of cognitive robotics. Topics covered include (but are not limited to) cognitive robotics, intelligent behaviors, systems intelligence, adaptive robotics, nature and bioinspiration, cognition architecture, cognitive modeling, knowledge representation, machine learning techniques, deep learning techniques, human-robot interaction, and evolutional robotics.

The six chapters contribute to the state-of-the-art and up-to-date knowledge on research advances in the field of cognition and robotics, introducing research at the interface between biology, sciences, engineering, and technology. With this book, we aim to develop a line of transformative research directions based on the adaptation of creative design and using intelligent methodologies, algorithms, and solutions. Tasks can be solved, and direct and indirect interaction with the task environment is developed by building evolving experiences through real-time learning. Cognitive robotics, AI, and machine learning allow researchers to think outside the box and open the way for new scientific challenges and developments.

> **Maki K. Habib** Mechanical Engineering Department, The American University in Cairo, New Cairo, Egypt

**1**

**Chapter 1**

**Abstract**

**1. Introduction**

in the 1970s in the USA [3].

*Diego Azevedo Leite*

The Neo-Mechanistic Model of

Human Cognitive Computation

The neo-mechanistic theory of human cognition is currently one of the most accepted major theories in fields, such as cognitive science and cognitive neuroscience. This proposal offers an account of human cognitive computation, and it has been considered by its proponents as revolutionary and capable of integrating research concerning human cognition with new evidence provided by fields of biology and neuroscience. However, some complex cognitive capacities still present a challenge for explanations constructed by using this theoretical structure. In this chapter, I make a presentation of some of the central tenets of this framework and show in what dimensions it helps our understanding of human cognition concerning aspects of capacities, such as visual perception and memory consolidation. My central goal, however, is to show that to understand and explain some particular human cognitive capacities, such as self-consciousness and some conscious informal reasoning and decision making, the framework shows substantial limitations. I conclude the chapter by suggesting that to fully understand human cognition we will need much

more than what the neo-mechanistic framework is actually able to provide.

A new intellectual movement in the field of cognitive science1

informal reasoning, decision making and action

**Keywords:** theoretical cognitive science, human cognitive computation, consciousness,

above all, in the last two decades of the current century, starting from debates that took place, mainly, in the philosophy of science at the end of the twentieth century. This movement has been described more broadly by many authors as a "new mechanistic philosophy" [4–7]. Strongly influenced by recent advances in computer science, neuroscience, and artificial intelligence, the theoretical framework developed by some

<sup>1</sup> I will use the term "cognitive science" in a *general sense* and a *specific sense*. In the general sense, the term will be treated as synonymous with the term "psychology" [1, 2]. In a specific sense, it will be treated as an attempt to build a science of cognition, integrating several different areas of knowledge, which took place

has been developed,

and Its Major Challenges

## **Chapter 1**
