Flowers have been of keen interest to humans throughout history, owing partly to the multitude of ways in which they stimulate our senses. Their brilliant colors, unusual patterns and shapes, and alluring fragrance enthrall humans and play a pivotal role in plant pollination. Surprisingly little is understood about why flowers are so complex, consisting of multiple components in multiple sensory modalities. In this project, the function of the multi-component floral signal in pollination is explored, using an integrative approach that addresses the pollinator's sensory and cognitive abilities and limitations. The main thesis of the research is that complex, multi-component signals convey information from plant to pollinator more reliably than simpler signals. To address this thesis, a laboratory-based model system involving bumble bees (Bombus impatiens) learning to forage for nectar rewards associated with color, shape, pattern and odor stimuli will be employed. Tests of learning and floral choice are guided by predictions, based in psychological and economic theory, about how signal complexity will affect the speed and accuracy of a bee's foraging behavior. Although the proposed work uses bees and flowers as a model system, the insights furnished by the work will contribute broadly to the study of animal communication and cognition. Additionally, results will contribute to a body of knowledge used to address an ongoing national crisis in crop pollination by bees. The project aims to mentor undergraduates from underrepresented groups and will include a bumble bee-oriented workshop on science careers targeted at high school students.