Formal models for reasoning are of outmost importance in the feld of Intelligent Systems. This special issue is focused on reasoning methods that involve the management of uncertainty or constraints, and its application in optimisation and decision-support problem
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretic...
International audienceEn 3 volumes : https://www.springer.com/gp/book/9783030061630 (vol.1) et https...
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretic...
International audienceMany problems in AI (in reasoning, planning, learning, perception and robotics...
Most intelligent systems have some form of decision making mechanisms built into their ...
This paper defines a logic model of optimization under uncertainty which optimizes the expectation o...
Accés lliure al text del llibre a la web de l'editorKnowledge, reasoning and learning (KRL) play a c...
Reasoning with uncertain information has received a great deal of attention recently, as this issue ...
[EN]The purpose of this workshop is to promote logical foundations for reasoning and learning under ...
http://www.sciencedirect.com/science/article/B6V8S-4KGPP34-2/1/b8b0563410520cbad9402d23e6ee42e
There is a significant range of ongoing challenges in artificial intelligence (AI) dealing with reas...
International audienceMany problems in AI require an intelligent agent to operate with incomplete or...
peer-reviewedIncreasingly we rely on machine intelligence for reasoning and decision making under un...
A logically uncertain reasoner would be able to reason as if they know both a programming lan-guage ...
AbstractThe use of support pairs associated with the facts and rules of a knowledge base of an exper...
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretic...
International audienceEn 3 volumes : https://www.springer.com/gp/book/9783030061630 (vol.1) et https...
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretic...
International audienceMany problems in AI (in reasoning, planning, learning, perception and robotics...
Most intelligent systems have some form of decision making mechanisms built into their ...
This paper defines a logic model of optimization under uncertainty which optimizes the expectation o...
Accés lliure al text del llibre a la web de l'editorKnowledge, reasoning and learning (KRL) play a c...
Reasoning with uncertain information has received a great deal of attention recently, as this issue ...
[EN]The purpose of this workshop is to promote logical foundations for reasoning and learning under ...
http://www.sciencedirect.com/science/article/B6V8S-4KGPP34-2/1/b8b0563410520cbad9402d23e6ee42e
There is a significant range of ongoing challenges in artificial intelligence (AI) dealing with reas...
International audienceMany problems in AI require an intelligent agent to operate with incomplete or...
peer-reviewedIncreasingly we rely on machine intelligence for reasoning and decision making under un...
A logically uncertain reasoner would be able to reason as if they know both a programming lan-guage ...
AbstractThe use of support pairs associated with the facts and rules of a knowledge base of an exper...
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretic...
International audienceEn 3 volumes : https://www.springer.com/gp/book/9783030061630 (vol.1) et https...
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretic...