• Publications
  • Influence
Knowledge Representation, Reasoning and Declarative Problem Solving
TLDR
Knowledge management and knowledge-based intelligence are areas of importance in today's economy and society, and their exploitation requires representation via the development of a declarative interface whose input language is based on logic. Expand
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Probabilistic reasoning with answer sets
TLDR
We develop a declarative language, P-log, that combines logical and probabilistic arguments in its reasoning. Expand
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Logic Programming and Knowledge Representation
TLDR
We consider extensions of the language of definite logic programs by classical (strong) negation, disjunction, and some modal operators and show how each of the added features extends the representational power of the languages. Expand
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Formalizing sensing actions A transition function based approach
TLDR
We develop a high-level action description language that allows specification of sensing actions and their effects in its domain description and allows queries with conditional plans. Expand
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Discovering drug–drug interactions: a text-mining and reasoning approach based on properties of drug metabolism
TLDR
We propose a novel approach of discovering DDIs through the integration of ‘biological domain knowledge’ with biological facts from Medline abstracts and curated sources. Expand
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Combining Multiple Knowledge Bases
TLDR
The authors define the concept of combining knowledge present in a set of knowledge bases and present algorithms to maximally combine them so that the combination is consistent with respect to the integrity constraints. Expand
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What to do and how to do it: Translating natural language directives into temporal and dynamic logic representation for goal management and action execution
TLDR
We describe an integrated robotic architecture that can achieve the above steps by translating natural language instructions incrementally and simultaneously into formal logical goal description and action languages, which can be used both to reason about the achievability of a goal as well as to generate new action scripts to pursue the goal. Expand
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Towards Addressing the Winograd Schema Challenge - Building and Using a Semantic Parser and a Knowledge Hunting Module
TLDR
We present an approach that identifies the knowledge needed to answer a challenge question, hunts down that knowledge from text repositories, and then reasons with them to come up with the answer. Expand
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Reasoning agents in dynamic domains
TLDR
The paper discusses an architecture for intelligent agents based on the use of A-Prolog- a language of logic programs under the answer set semantics. Expand
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