Cognitive Modeling, Symbolic

(1995). Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory. Distributed memory and the representation of general and specific information. On the interaction of selective attention and lexical knowledge: a connectionist account of neglect dyslexia. Implicit and explicit memory in amnesia: some explanations and predictions of the tracelink model. On language and connectionism: analysis of a parallel distributed processing model of language acquisition. From rote learning to system building: acquiring verb morphology in children and connectionist nets. From simple associations to systematic reasoning: a connectionist representation of rules, variables and dynamic bindings using temporal synchrony. Constituent attachment and thematic role assignment in sentence processing: influences of content-based expectations. Symbolic cognitive models are theories of human cognition that take the form of working computer programs. A cogni-tive model is intended to be an explanation of how some aspect of cognition is accomplished by a set of primitive computational processes. A model performs a specific cog-nitive task or class of tasks and produces behavior that constitutes a set of predictions that can be compared to data from human performance. Task domains that have received considerable attention include problem solving, language comprehension, memory tasks, and human-device interaction. The scientific questions cognitive modeling seeks to answer belong to cognitive psychology, and the computational techniques are often drawn from artificial intelligence. Cognitive modeling differs from other forms of