Robust reasoning: integrating rule-based and similarity-based reasoning

Robust Reasoning: Integrating Rule-Based and Similarity-Based Reasoning

DANIEL: Integrating Case-Based and Rule-Based Reasoning in Law

Motivation This paper introduces DANIEL,1 an architecture for the integration of case-based reasoning and rule-based reasoning for legal interpretation. Rather than interleaving the reasoners and assuming their complementarity, like in previous approaches, they are applied concurrently. Conflicting interpretations are handled explicitly, based on domain knowledge and on the notion of redundancy...

"integrating Case Based and Rule Based Reasoning: the Possibilistic

Rule based reasoning (RBR) and case based reasoning (CBR) have emerged as two important and complementary reasoning methodologies in artificial intelligence (AI). For problem solving in complex, real world situations, it is useful to integrate RBR and CBR. This paper presents an approach to achieve a compact and seamless integration of RBR and CBR within the base architecture of rules. The pape...

Integrating case-based and rule based reasoning: the possibilistic connection

Rule based reasoning (RBR) and case based reasoning (CBR) have emerged as two impor­ tant and complementary reasoning methodolo­ gies in artificial intelligence (AI). For problem solving in complex, real world situations, it is useful to integrate RBR and CBR. This paper presents an approach to achieve a compact and seamless integration of RBR and CBR within the base architecture of rules. The ...

INTEGRATING CASE-BASED REASONING, KNOWLEDGE-BASED APPROACH AND TSP ALGORITHM FOR MINIMUM TOUR FINDING

Imagine you have traveled to an unfamiliar city. Before you start your daily tour around the city, you need to know a good route. In Network Theory (NT), this is the traveling salesman problem (TSP). A dynamic programming algorithm is often used for solving this problem. However, when the road network of the city is very complicated and dense, which is usually the case, it will take too long fo...