Recent developments in game theory incorporate assumptions about the players' beliefs, bounded rationality, knowledge, and information processing that are of special interest to cognitive scientists studying higher cognitive processes. This article outlines some of these developments, and then describes in some detail two new streams of experimental research on subjective randomization and strategic reasoning driven by these developments.

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Following the major paradigm shift from group selection to gene selection, game theoretical approach came into the study of animal behaviour as a powerful tool. Vast aspects of animal beheaviour are thought to be under one or other kind of game situation, and under those circumstances, evolutionary game theory often predicts the coexistence of more than 2 different strategies in one population. Evolutionarily Stable Strategy is the key concept to understand those situations. Game theoretical approaches have played an important role in the study of animal conflict, communication, cooperation, habitat selection, etc. In traditional game theory which are used in social sciences, strategies are assumed to be adopted by rational choice. In evolutionary game theory, each strategy has a genetic basis and the outcome of the competition among them are determined through natural selection. In the analysis of human behaviour, it is not yet clear what is the basic adaptive architecture of the workings of our brain and how cultural contexts insert influence on them. Nor are we yet successful to give full scientific explanation to the origin and maintenance of different types of cultures. However, evolutionary game theory makes a host of testable predictions about human behavioural diversity. It will be productive both for behavioural ecology and human social sciences to reconsider human behaviour from the evolutionary perspective.

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Three experiments investigated accuracy of discerning defectors from cooperators in one-shot prisoner's dilemma games. The prisoner's dilemma games were constructed in a manner that represented a typical social exchange situation. Overall, participants who were classmates and had known each other fairly well for the last few months failed to discern, better than chance, who cooperated and who defected in the prisoner's dilemma. Furthermore, it was shown that high-trusters were more accurate in cheater detection when the game was played anonymously, whereas those who were high in social anxiety were more accurate when the game was played between mutually identified players. The latter type of participants were also more accurate in judging the nature of interpersonal relations (who liked whom) in their class. Those findings were interpreted to represent two types of adaptive strategy for those who faces socially uncertain situations.

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How does a reciprocal communal sharing system come into existence in a sustainable form in human societies? The anthropological literature has provided two explanations for the origin of communal sharing under uncertainty: risk reduction by social sharing (Kaplan & Hill, 1985) and tolerated theft (Blurton Jones, 1984, 1987; Winterhalder, 1986, 1996). In this paper, we aim to develop a third explanation focusing on the emergence of a communal sharing norm. A communal sharing norm here refers to a social norm designating uncertain resources as common properties. A series of computer simulations based on an evolutionary game framework suggests that such a communal sharing norm is indeed evolvable. We argue that the evolutionary game analysis can be a powerful tool in cognitive science to derive empirical hypotheses concerning various cognitive and behavioral mechanisms.

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The use of spatial expressions always involves some degree of ambiguity. Some of the ambiguity is quantitative. For example, when someone says, “the ball is to the LEFT of the yellow car”, it is not obvious how we can determine the area which is “the LEFT of” the car. Where in the space does “LEFT” end and “FRONT” start? Other type of amibiguity is qualitative. In the above example, we even cannot assume that the speaker and the hearer have the same spatial relation in mind. Did the speaker say LEFT meaning LEFT with respect to the speaker, or LEFT with respect to the car's front?
Two different perspective systems underlie the semantics of basic spatial terms such as FRONT/BACK/LEFT/RIGHT. One system uses the viewer as the frame of reference (the deictic system), while the other system takes one object as the frame of reference and describes other objects with respect to this reference object (the intrinsic system). As shown in the “to the left of the car” example above, these two systems yield very different interpretation of the spatial layout in some situations. Although this fact has been long noted by many researchers (e.g., Clark, 1973; Fillmore, 1975; Levelt, 1982; Levinson, 1996), how people select one system over the other under various circumstances still needs to be explored (Franklin, Tversky, & Coon, 1992). In this research, by setting up an experiment using a 3-D model space in a computer display, we empirically examined how people determined the assignment of FRONT/BACK/LEFT/RIGHT in various contexts including different types of reference objects as well as different orientations these objects were placed with respect to the perspective of the viewer. We found that at least four factors, (1) characteristics of the reference object; (2) orientation of the reference object with respect to the viewer; (3) position of the referred object with respect to the reference object; (4) mode of presentation, are involved when people select one perspective system over the other, and furthermore, there is a complex interaction among these factors. We also examined the boundaries of the four terms. We found that the four terms did not evenly divide the given space. BACK in general covered a larger area than the other three terms, but the division of the space by the four terms are dynamically affected by the orientation of the reference object.

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This study investigated how our recognition space changes due to acquisition of categorical knowledge. Thus far, many studies on categorization have used arbitrary features as relevant dimensions for categorization. In our study we defined the relevant dimension as the principal component feature that is found in human recognition space. Recognition space was examined by two tasks, a similarity estimation task and a task in which a momentary stimulus is presented for identification. When the task was similarity estimation, after category learning, the recognition space changed as the stimuli which belong to the same category concentrate on one point. But in the identification task, which is thought not to be affected by higher level knowledge, this type of strong change was not observed. And the recognition space change was not a simple change in the relevant dimension, but rather each category group changed independently.

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