What should I do next? Using shared representations to solve interaction problems
What should I do next? Using shared representations to solve interaction problems
复制标题
DOI：
10.1007/s00221-011-2712-1
复制
发表时间：
2011-06-01
影响因子：
2
通讯作者：
Dindo, Haris
中科院分区：
文献类型：
--
作者：
Pezzulo, Giovanni;Dindo, Haris
对“社会心理”如何工作的研究表明，参与联合行动的认知主体积极估计和影响他人的认知变量，并与他们形成共同的表征。(How)共享表示是否增强了协调？在本文中，我们提供了一个概率模型的联合行动，强调如何共享表示帮助解决相互作用的问题。我们关注模型的两个方面。首先，我们讨论如何共享表示允许协调的认知变量（信念，意图和行动）的水平，并确定一个连贯的展开的行动执行和预测过程中的两个代理人的大脑。第二，我们讨论了信号行动的重要性，作为战略的一部分，为共享表示和积极指导他人的行动，以实现一个共同的目标。此外，我们呈现了人机实验（塔游戏）的数据，其中两个代理（人类和计算机）必须一起建造一座由彩色块制成的塔，但只有人类知道要建造的塔的星座（例如，红蓝红蓝我们报告的证据表明，人类使用的信号策略，考虑到另一个的不确定性，反过来，我们的模型能够使用人类的行动作为线索，以“调整”其表示，并选择互补的行动。
Studies on how "the social mind" works reveal that cognitive agents engaged in joint actions actively estimate and influence another's cognitive variables and form shared representations with them. (How) do shared representations enhance coordination? In this paper, we provide a probabilistic model of joint action that emphasizes how shared representations help solving interaction problems. We focus on two aspects of the model. First, we discuss how shared representations permit to coordinate at the level of cognitive variables (beliefs, intentions, and actions) and determine a coherent unfolding of action execution and predictive processes in the brains of two agents. Second, we discuss the importance of signaling actions as part of a strategy for sharing representations and the active guidance of another's actions toward the achievement of a joint goal. Furthermore, we present data from a human-computer experiment (the Tower Game) in which two agents (human and computer) have to build together a tower made of colored blocks, but only the human knows the constellation of the tower to be built (e.g., red-blue-red-blue-...). We report evidence that humans use signaling strategies that take another's uncertainty into consideration, and that in turn our model is able to use humans' actions as cues to "align" its representations and to select complementary actions.