P-log: Probabilistic Reasoning with Answer Set Programming

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P-log P-log P-log [Baral, Gelfond, Rushton 09]: main idea possible worlds = answer sets of a (probabilistic) logic program. The syntax is close to ASP. We allow atoms of the form a(t) = v where a is a functional attribute, t a tuple of terms and v a value in the range of a(t). P. Cabalar ( Depto. Computación P-log University of Corunna, SPAIN ) May 9, 2013 17 / 25
P-log P-log P-log [Baral, Gelfond, Rushton 09]: main idea possible worlds = answer sets of a (probabilistic) logic program. The syntax is close to ASP. We allow atoms of the form a(t) = v where a is a functional attribute, t a tuple of terms and v a value in the range of a(t). We can declare sorts and types for function arguments and range. P. Cabalar ( Depto. Computación P-log University of Corunna, SPAIN ) May 9, 2013 17 / 25
Page 1 and 2: P-log: Probabilistic Reasoning with
Page 3 and 4: Introduction 1 Introduction 2 P-log
Page 5 and 6: Motivation Introduction Probability
Page 7 and 8: Motivation Introduction Probability
Page 9 and 10: Introduction Example 1. Monty Hall
Page 11 and 12: Introduction Example 1. Monty Hall
Page 13 and 14: Introduction Example 2. Simpson’s
Page 21 and 22: Introduction Probabilistic Reasonin
Page 23 and 24: Introduction Probabilistic models S
Page 25 and 26: Probabilistic models Introduction S
Page 27 and 28: Probabilistic models Introduction I
Page 29 and 30: Introduction Probabilistic models I
Page 31: P-log P-log P-log [Baral, Gelfond,
Page 35 and 36: P-log P-log P-log [Baral, Gelfond,
Page 37 and 38: P-log The jungle example in P-log %
Page 39 and 40: P-log The jungle example in P-log W
Page 41 and 42: P-log Causal probability statements
Page 43 and 44: P-log Causal probability statements
Page 45 and 46: P-log Observations and intervention

P-log: Probabilistic Reasoning with Answer Set Programming

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