1,303 research outputs found
How much of commonsense and legal reasoning is formalizable? A review of conceptual obstacles
Fifty years of effort in artificial intelligence (AI) and the formalization of legal reasoning have produced both successes and failures. Considerable success in organizing and displaying evidence and its interrelationships has been accompanied by failure to achieve the original ambition of AI as applied to law: fully automated legal decision-making. The obstacles to formalizing legal reasoning have proved to be the same ones that make the formalization of commonsense reasoning so difficult, and are most evident where legal reasoning has to meld with the vast web of ordinary human knowledge of the world. Underlying many of the problems is the mismatch between the discreteness of symbol manipulation and the continuous nature of imprecise natural language, of degrees of similarity and analogy, and of probabilities
Systematicity and surface similarity in the development of analogy
In split page format (number of pages: 45)Includes bibliographical reference
Introducing a Context-Aware Scheme in an intelligent reasoning process
Several investigations have been developed around analogies based reasoning in different domains, however the analogy between arguments has not been deeply explored. A semiformal way to express these patterns of reasoning were proposed by Walton, through argument schemes from analogy. From this, it is possible to propose computable approximations for comparing arguments. In this paper we introduce a formalism based on the comparison of arguments through descriptors or labels which describes an aspect that the argument refers to. This formalism allows us classifying similar arguments considering the natural descriptors of them, in a specific context.XVII Workshop Agentes y Sistemas Inteligentes (WASI).Red de Universidades con Carreras en Informática (RedUNCI
Introducing a Context-Aware Scheme in an intelligent reasoning process
Several investigations have been developed around analogies based reasoning in different domains, however the analogy between arguments has not been deeply explored. A semiformal way to express these patterns of reasoning were proposed by Walton, through argument schemes from analogy. From this, it is possible to propose computable approximations for comparing arguments. In this paper we introduce a formalism based on the comparison of arguments through descriptors or labels which describes an aspect that the argument refers to. This formalism allows us classifying similar arguments considering the natural descriptors of them, in a specific context.XVII Workshop Agentes y Sistemas Inteligentes (WASI).Red de Universidades con Carreras en Informática (RedUNCI
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Rationality in context: An analogical perspective
At times, human behavior seems erratic and irrational. Therefore, when modeling human decision-making, it seems reasonable to take the remarkable abilities of humans into account with respect to rational behavior, but also their apparent deviations from the normative standards of rationality shining up in certain rationality tasks. Based on well-known challenges for human rationality, together with results from psychological studies on decision-making and from previous work in the field of computational modeling of analogy-making, I argue that the analysis and modeling of rational belief and behavior should also consider context-related cognitive mechanisms like analogy-making and coherence maximization of the background theory. Subsequently, I conceptually outline a high-level algorithmic approach for a Heuristic Driven Theory Projection-based system for simulating context-dependent human-style rational behavior. Finally, I show and elaborate on the close connections, but also on the significant differences, of this approach to notions of "ecological rationality"
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