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109
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ECAI
2004
Springer
15 years 8 months ago
Combining Multiple Answers for Learning Mathematical Structures from Visual Observation
Learning general truths from the observation of simple domains and, further, learning how to use this knowledge are essential capabilities for any intelligent agent to understand ...
Paulo Santos, Derek R. Magee, Anthony G. Cohn, Dav...
119
Voted
ICML
2005
IEEE
16 years 3 months ago
Learning the structure of Markov logic networks
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. In this pap...
Stanley Kok, Pedro Domingos
168
Voted
HYBRID
2010
Springer
15 years 4 months ago
Receding horizon control for temporal logic specifications
In this paper, we describe a receding horizon scheme that satisfies a class of linear temporal logic specifications sufficient to describe a wide range of properties including saf...
Tichakorn Wongpiromsarn, Ufuk Topcu, Richard M. Mu...
239
Voted
EH
1999
IEEE
351views Hardware» more  EH 1999»
15 years 7 months ago
Evolvable Hardware or Learning Hardware? Induction of State Machines from Temporal Logic Constraints
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
170
Voted
KR
1991
Springer
15 years 6 months ago
Meta-Reasoning in Executable Temporal Logic
Temporal logic can be used as a programming language. If temporal formulae are represented in the form of an implication where the antecedent refers to the past, and the consequen...
Howard Barringer, Michael Fisher, Dov M. Gabbay, A...