Dataset Information

Domain learning naming game for color categorization.

ABSTRACT: Naming game simulates the evolution of vocabulary in a population of agents. Through pairwise interactions in the games, agents acquire a set of vocabulary in their memory for object naming. The existing model confines to a one-to-one mapping between a name and an object. Focus is usually put onto name consensus in the population rather than knowledge learning in agents, and hence simple learning model is usually adopted. However, the cognition system of human being is much more complex and knowledge is usually presented in a complicated form. Therefore, in this work, we extend the agent learning model and design a new game to incorporate domain learning, which is essential for more complicated form of knowledge. In particular, we demonstrate the evolution of color categorization and naming in a population of agents. We incorporate the human perceptive model into the agents and introduce two new concepts, namely subjective perception and subliminal stimulation, in domain learning. Simulation results show that, even without any supervision or pre-requisition, a consensus of a color naming system can be reached in a population solely via the interactions. Our work confirms the importance of society interactions in color categorization, which is a long debate topic in human cognition. Moreover, our work also demonstrates the possibility of cognitive system development in autonomous intelligent agents.

SUBMITTER: Li D

PROVIDER: S-EPMC5685623 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Domain learning naming game for color categorization.

Li Doujie D Fan Zhongyan Z Tang Wallace K S WKS

PloS one 20171114 11

Naming game simulates the evolution of vocabulary in a population of agents. Through pairwise interactions in the games, agents acquire a set of vocabulary in their memory for object naming. The existing model confines to a one-to-one mapping between a name and an object. Focus is usually put onto name consensus in the population rather than knowledge learning in agents, and hence simple learning model is usually adopted. However, the cognition system of human being is much more complex and know ...[more]

PMID: 29136661

Similar Datasets

Project description:Categorization learning is a fundamental and complex cognitive ability. The present EEG study examined how much action video gamers differ from non-gamers in the usage of visual exploration and attention driven perceptual analyses during a categorization learning task. Seventeen healthy right-handed non-gamers and 16 healthy right-handed action video gamers performed a visual categorization task with 14 ring stimuli, which were divided into two categories. All stimuli had the same structure but differed with respect to their color combinations and were forming two categories including a prototype, five typical stimuli and one exception. The exception shared most similarities with the prototype of the opposite group. Prototypes and typical stimuli were correctly categorized at an early stage of the experiment, whereas the successful categorization of exceptions occurred later. The behavioral data yield evidence that action video gamers perform correct categorizations of exceptions earlier than non-gamers. Additionally, groups differed with respect to differential expressions of the attention related P150 ERP component (early perceptual analysis) and the N170 ERP component, which reflected differential processing demands for the stimulus material. In comparison to non-gamers, the analyses of the eye movements yield for action video gamers different, more central fixations possibly indicating covert peripheral processing. For both groups fixations as well as saccades decrease and in the case of exceptions, one of the two segments that are decisive for correct categorization shows higher fixation rates at the end of the experiment. These findings indicate for both groups a learning process regarding the stimulus material. Regarding the group differences, we interpret the results to indicate that action video gamers show a different stimulus exploration, use an enhanced early perceptual analysis of the stimulus material and therefore may detect changes in objects faster and learned the belonging of the stimuli to their categories in an earlier trial phase.

Dataset Information

Domain learning naming game for color categorization.

Publications

Domain learning naming game for color categorization.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets