This paper reexamines Masanao Toda's models of civilization and his urge theory presented in his book Man, Robot and Society (Toda, 1982). Although many of Toda's models and speculations match what we have found in the history, we suggest reinterpretations of his concepts of the second law of civilization and excess energy based on some recent literature on civilizations that collapsed in the human history as well as what we find in modern societies 50 years after his writings. Reconstructing his models with ecological reconsideration sheds light on some fundamental problems of industrial societies that not only exploited natural resources but also created professional modules that have suppressed our natural potentials and passions for creating our daily lives. We propose an LDP (local domestic products) approach to these problems by integrating Toda's urge theory with Wilber' s theory of evolution, where networks of individuals share creative activities in their own contexts using their local resources.

Cognitive science is a framework for understanding human behavior using the metaphor of a computational machine. Computational neuroscience has also taken the approach of using mathematical algorithms to reveal the computational mechanisms of the brain. In this paper, we review an approach to reveal the computational mechanisms of the brain using reinforcement learning to explain behaviors, especially those related to reward learning and decision making, and its implications for the surrounding fields. Computational modeling with reinforcement learning provides a novel way of understanding and applications not only in neuroscience but also in various surrounding fields such as psychology, economics, marketing, and psychiatry. Finally, we will discuss the limitations of the mathematical approach to understanding the brain and the future direction of cognitive science.

Considering the future development of cognitive science, I feel the necessity of a big hypothesis. So, in this paper, I present a hypothesis on a brain mechanism of logical inference that is a specific feature of human thinking as a challenge for cognitive science. This hypothesis may give a large impact as it includes the model elements relating to the origin of emotion and consciousness that are specific to the human mind.

Toda assumes that the system of emotions is a survival software that dictates to people a proper coping behavior in each situation, and proposes the urge system based on the assumption. Our research has focused on autonomous systems with emotion, and has aimed to develop an autonomous system using an emotion model. Among autonomous systems, our research has focused, in particular, on a self sufficient system that can, for example, supply its own energy to itself. This paper introduces a self sufficient system using the urge system and applies the system to a robot Babyloid that satisfies its sufficiency by itself. This paper also explains the effects of the psychological interaction between the robot and the user.

This is a short essay based on the author's tiny experience of cognitive science study. It argues that traditional methods of cognitive science such as production system, protocol analysis, questionnaire through crowd sourcing to name a few are not enough for unraveling detailed mechanism of cognition and thought processes in our brain. After checking pros and cons of these traditional methods, new methodologies are speculated. These new methodologies will use machine learning, the Internet, and robots to their maxima. They try to gather massive recordings of our daily sensory data plus our internal reactions. Recent rapid progress in sensor technologies and machine learning makes it possible to create (i) tools to gather an unprecedented amount of sensory data and (ii) robots which facilitate such massive data gathering.

In this paper, the author first reviews the history of cognitive science and explains that the view of human beings presented by cognitive science can be interpreted as a transition from the Cartesian to the Spinozistic view. The author then explains that there are two major schools of thought in the cognitive science community as to whether the method for clarifying the Spinozistic view of human nature is the Cartesian method of modern science or not, which is an extension of Toda's view of cognitive science vs. Hatano's concern about it. On the other hand, with the recent dramatic development of mathematical and statistical methods, especially computational modeling of human behavioral data, it is possible to elucidate Spinozistic view of human nature using modern scientific methods, and the author will express his personal view that this may be an approach to the reproducibility problem which has recently become an issue in the psychology community. Finally, the author will discuss how cognitive science should get along with AI, which has been making dramatic progress in recent years.

In this paper, I give an overview of the various predictions presented in The future of psychology by Toda (1971) from the perspective of the present, which is indeed a distant future from that time. In particular, the following aspects were briefly addressed: external pressures on the development of psychology, theories of psychology, psychology and technology, and collaboration in psychology. Based on the current understanding of these issues, the future of psychology as seen from now is discussed: it will probably be characterized as a convergence of machine learning, advances in technology related to our research practices, and large-scale collaboration involving citizens. This paper concludes that thinking about the future of psychology is the same as thinking about what the identity of psychologists is and how psychology can survive.

In his seminal paper Possible roles of psychology in the very distant future, Masanao Toda has given his perspective on the long-term development of our society, science, and technology. In his perspective, which I call the development-in-parallel hypothesis, human-social science was expected to develop in parallel to the development of natural science. In contrast to this hypothesis, I will propose the development-in-nested-structure hypothesis, which states that natural science on general things is needed to launch information science on computer as a special class of things, and information science on general computers is needed to launch cognitive science on brain as a special class of computers. I discuss the possible roles of cognitive science in the future: Cognitive science needs to play a central role in leading the third class of science.

This article aims to scrutinize the contents of two papers published in 1951 by Masanao Toda, the one arguing a general framework for human behavior and the other concerning a measurement of intuitive probability. Although Masanao Toda is recognized as a pioneer of cognitive science in Japan, his works prior to those on cognitive science are not familiar to the Japanese cognitive science community; thus, the fact, that he was also a pioneer of decision-making research in Japan, is not sufficiently recognized. This paper demonstrates several interesting and ingenious features of the two papers published early in Toda's career that concern an issue of intuitive judgment in terms of research trends both in those days and since. Finally, this paper also argues for the significance of examining Toda's studies in reconsidering the origin of both behavioral economics and cognitive science.

This paper will discuss a role of anger from the perspective of game theory. Primarily, by adopting a responder in a standard ultimatum game as an example, we highlight that anger has a rational role as a commitment device and a signaling device from an evolutional point of view. Game theory has clarified theoretical conditions, such as incentive compatibility, to make a commitment and/or signaling function. However, there are few arguments as to whether emotions such as anger satisfy those requirements. Thus, in this paper, we show that anger expressed by the responder who was offered an unfair offer in an ultimatum game actually satisfies those requirements.

In order to clarify how a practical research community functions as Toda's theorizing model, this article reported two studies on a design-based implementation research (DBIR) project being jointly implemented by CoREF and regional boards of education. Participating teachers from various districts have been improving their lessons and assessments through generating and sharing hypotheses on learner-centered lessons conducted through the Knowledge Constructive Jigsaw method. Study 1 analyzed the system design of the community in order to extract basic elements to embody Toda's concept of the theorizing model. Study 2 reported the redesign of a lesson study system, the lack of which had been pointed out in Study 1, and verified how the system helped teachers generate hypotheses of student learning by connecting accumulated design principles as constituent theories and revise them based on evidence of student learning. In order for the practical research community to function as the theorizing model, two studies led us to extract four elements: 1) an instructional framework and database of lessons to connect a theoretical framework, actual practices, and constituent theories, 2) a mechanism enabling teachers to become conscious of hypotheses on lesson designs, 3) a mechanism to make complex processes of student learning visible, and 4) a mechanism to foster collaborative reflection. Though being situated, context-dependent, and emergent, the practical research community was considered as a candidate for the theorizing model, inspiring others to design another community as well as to delve into the concrete features of a unified science for societal problem solving.