NEUROLINGUISTICALLY CONSTRAINED SIMULATION OF SENTENCE COMPREHENSION: INTEGRATING ARTIFICIAL INTELLIGENCE AND BRAIN THEORY

• Main Author: GIGLEY, HELEN MUELLER
• Language: ENG
• Published: ScholarWorks@UMass Amherst 1982
• Subjects: Computer science|Information Systems
• Online Access: https://scholarworks.umass.edu/dissertations/AAI8229553

An artificial intelligence approach to the simulation of neurolinguistically constrained processes in sentence comprehension is developed using control strategies for simulation of cooperative computation in associative networks. The desirability of this control strategy in contrast to ATN and production system strategies is explained. A first pass implementation of HOPE, an artificial intelligence simulation model of sentence comprehension, constrained by studies of aphasic performance, psycholinguistics, neurolinguistics, and linguistic theory is described. Claims that the model could serve as a basis for sentence production simulation and for a model of language acquisition as associative learning are discussed. HOPE is a model that performs in a "normal" state and includes a "lesion" simulation facility. HOPE is also a research tool. Its modifiability and use as a tool to investigate hypothesized "causes" of degradation in comprehension performance by aphasic patients are described. Issues of using behavioral constraints in modelling and obtaining appropriate data for simulated process modelling are discussed. Finally, problems of validation of the simulation results are raised; and issues of how to interpret clinical results to define the evolution of the model are discussed. Conclusions with respect to the feasibility of artificial intelligence simulation process modelling are discussed based on the current state of the research. The significance of the research for artificial intelligence techniques, the need for AI simulation models, the use of such models as investigative tools, the potential use for enriching our understanding of the brain and its function, and the potential for contributing to better understanding of aphasic performance leading to enhanced therapy, together suggest many exciting prospects for future development.