Logic vs. Semantic Networks

1. 2 papers on the relationship between first-order logic and semantic networks:
   • Schubert, Lenhart K. (1991), "Semantic Nets Are in the Eye of the Beholder", in John F. Sowa (ed.), Principles of Semantic Networks: Explorations in the Representation of Knowledge (San Mateo, CA: Morgan Kaufmann): 95-107.

   • Shastri, Lokendra (1991), "Why Semantic Networks?", in John F. Sowa (ed.), Principles of Semantic Networks: Explorations in the Representation of Knowledge (San Mateo, CA: Morgan Kaufmann): 109-136.

2. 2 papers (and a review) on the difficulty of representing knowledge about knowledge in FOL:
   • des Rivières, Jim, & Levesque, Hector J. (1986), "The Consistency of Syntactical Treatments of Knowledge", in Joseph Y. Halpern (ed.), Theoretical Aspects of Reasoning about Knowledge: Proceedings of the 1986 Conference (TARK-86; Monterey, CA) (Los Altos, CA: Morgan Kaufmann): 115-130.

   • Asher, Nicholas M., & Kamp, Johan A.W. (1986), "The Knower's Paradox and Representational Theories of Attitudes", in Joseph Y. Halpern (ed.), Theoretical Aspects of Reasoning about Knowledge: Proceedings of the 1986 Conference (TARK-86; Monterey, CA) (Los Altos, CA: Morgan Kaufmann): 131-147.
     • Rapaport, William J. (1988), Review of Joseph Y. Halpern (ed.), Theoretical Aspects of Reasoning About Knowledge: Proceedings of the 1986 Conference (Los Altos, CA: Morgan Kaufmann, 1986), Journal of Symbolic Logic 53: 660-670.

3. 3 papers on how SNePS handles the problem:
   • Barnden, John A. (1986), "A Viewpoint Distinction in the Representation of Propositional Attitudes", Proceedings of the 5th National Conference on Artificial Intelligence (AAAI-86, Philadelphia) (Los Altos, CA: Morgan Kaufmann), Vol. 1, pp. 411-415.

   • Shapiro, Stuart C., & Rapaport, William J. (1991), "Models and Minds: Knowledge Representation for Natural-Language Competence", in Robert Cummins & John Pollock (eds.), Philosophy and AI: Essays at the Interface (Cambridge, MA: MIT Press): 215-259.

     Abstract: Cognitive agents, whether human or computer, that engage in natural-language discourse and that have beliefs about the beliefs of other cognitive agents must be able to represent objects the way they believe them to be and the way they believe others believe them to be. They must be able to represent other cognitive agents both as objects of beliefs and as agents of beliefs. They must be able to represent their own beliefs, and they must be able to represent beliefs as objects of beliefs. These requirements raise questions about the number of tokens of the belief representation language needed to represent believers and propositions in their normal roles and in their roles as objects of beliefs. In this paper, we explicate the relations among nodes, mental tokens, concepts, actual objects, concepts in the belief spaces of an agent and the agent's model of other agents, concepts of other cognitive agents, and propositions. We extend, deepen, and clarify our theory of intensional knowledge representation for natural-language processing, as presented in previous papers and in light of objections raised by others. The essential claim is that tokens in a knowledge-representation system represent only intensions and not extensions. We are pursuing this investigation by building CASSIE, a computer model of a cognitive agent and, to the extent she works, a cognitive agent herself. CASSIE's mind is implemented in the SNePS knowledge-representation and reasoning system.

   • Shapiro, Stuart C. (1993), "Belief Spaces as Sets of Propositions", Journal of Experimental and Theoretical Artificial Intelligence 5(2&3): 225-235.