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Even More AI!
Published in Nicolas Sabouret, Lizete De Assis, Understanding Artificial Intelligence, 2020
In the 1960s, John McCarthy and Patrick Hayes laid the foundations for an entire field of symbolic artificial intelligence. They proposed a model for reasoning about actions and changes: things are no longer always true or always false. In so doing, they paved the way for cognitive robotics research – in other words, building robots capable of reasoning about how to behave in the world. This isn’t quite artificial consciousness, however, because the machines simply apply rules of mathematical logic within a framework whose bounds have been set by humans. However, the systems developed using this technology are able to adapt to different situations by using logical reasoning.
Special issue on symbol emergence in robotics and cognitive systems (II)
Published in Advanced Robotics, 2022
Tadahiro Taniguchi, Takayuki Nagai, Shingo Shimoda, Angelo Cangelosi, Yiannis Demiris, Yutaka Matsuo, Kenji Doya, Tetsuya Ogata, Lorenzo Jamone, Yukie Nagai, Emre Ugur, Daichi Mochihashi, Yuuya Unno, Kazuo Okanoya, Takashi Hashimoto
Innovations in artificial intelligence have opened the door to the next generation of cognitive robotics. Indeed, deep learning and statistical machine learning provide a wide range of cognitive modules, e.g. image and speech recognition, localization and mapping, natural language processing, and motion planning. However, most of the achievements in artificial intelligence are made in computer and simulation environments. In contrast with the conventional artificial intelligence that is optimized with large amounts of prepared data, we, human beings, learn a variety of skills and knowledge from our own sensorimotor experiences. To develop a cognitive and developmental robot that can learn and adapt in real environments, we still have a huge number of challenges because the world is full of uncertainty and dynamic changes. Also, emphasizing the developmental aspects of cognition is important to understand the developmental process of human cognitive systems.
What is the role of the next generation of cognitive robotics?
Published in Advanced Robotics, 2022
Shingo Shimoda, Lorenzo Jamone, Dimitri Ognibene, Takayuki Nagai, Alessandra Sciutti, Alvaro Costa-Garcia, Yohei Oseki, Tadahiro Taniguchi
What are the key issues for continuous control with uncertainties? In the round table, several important candidates for the key issues were raised, namely, generalization, active sensing, prediction and language communication. In this review paper, we discuss these topics focusing on continuous control with uncertainties. As mentioned above, the approaches to establish these functions without stopping robot control in the real world is the key problem for cognitive robotics. The discussions in this paper review the various system for cognitive robotics from this point of view and derive a future direction for research on cognitive robotics. Artificial intelligence based on machine learning is also an important tool for cognitive robotics. How to use various types of tools in continuous control is also an important target of discussion.
Special issue on Symbol Emergence in Robotics and Cognitive Systems (I)
Published in Advanced Robotics, 2022
Tadahiro Taniguchi, Takayuki Nagai, Shingo Shimoda, Angelo Cangelosi, Yiannis Demiris, Yutaka Matsuo, Kenji Doya, Tetsuya Ogata, Lorenzo Jamone, Yukie Nagai, Emre Ugur, Daichi Mochihashi, Yuuya Unno, Kazuo Okanoya, Takashi Hashimoto
Innovations in artificial intelligence have opened the door to the next generation of cognitive robotics. Indeed, deep learning and statistical machine learning provide a wide range of cognitive modules, e.g. image and speech recognition, localization and mapping, natural language processing, and motion planning. However, most of the achievements in artificial intelligence are made in computer and simulation environments. In contrast with the conventional artificial intelligence that is optimized with large amounts of prepared data, we, human beings, learn a variety of skills and knowledge from our own sensorimotor experiences. To develop a cognitive and developmental robot that can learn and adapt in real environments, we still have a huge number of challenges because the world is full of uncertainty and dynamic changes. Also, emphasizing the developmental aspects of cognition is important to understand the developmental process of human cognitive systems.