An Analysis and Comparison of ACT-R and Soar
This work provides a detailed comparison for researchers in cognitive science and AI, but it is incremental as it synthesizes existing knowledge without introducing new methods or results.
The paper analyzes and compares the ACT-R and Soar cognitive architectures, focusing on their structures, memory representations, and processing, while identifying commonalities and differences in agent data, metadata, and meta-process data.
This is a detailed analysis and comparison of the ACT-R and Soar cognitive architectures, including their overall structure, their representations of agent data and metadata, and their associated processing. It focuses on working memory, procedural memory, and long-term declarative memory. I emphasize the commonalities, which are many, but also highlight the differences. I identify the processes and distinct classes of information used by these architectures, including agent data, metadata, and meta-process data, and explore the roles that metadata play in decision making, memory retrievals, and learning.