By Kryštof Hoder, Laura Kovács, Andrei Voronkov (auth.), Ildar Batyrshin, Grigori Sidorov (eds.)
The two-volume set LNAI 7094 and LNAI 7095 constitutes the refereed complaints of the tenth Mexican overseas convention on man made Intelligence, MICAI 2011, held in Puebla, Mexico, in November/December 2011. The ninety six revised papers awarded have been rigorously reviewed and chosen from a number of submissions. the 1st quantity comprises 50 papers representing the present major subject matters of curiosity for the AI neighborhood and their purposes. The papers are prepared within the following topical sections: automatic reasoning and multi-agent platforms; challenge fixing and desktop studying; typical language processing; robotics, making plans and scheduling; and scientific purposes of synthetic intelligence.
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Extra info for Advances in Artificial Intelligence: 10th Mexican International Conference on Artificial Intelligence, MICAI 2011, Puebla, Mexico, November 26 - December 4, 2011, Proceedings, Part I
Second, we obtain the M M r Characterization of Argumentation Semantics in Terms of the M M r Semantics 25 models of ΨAF . Finally, we use the mapping f of Deﬁnition 9, to obtain the preferred argumentation semantics of AF . In this way, mapping f assigns to each M M r model of ΨAF a set of arguments from the argumentation framework AF . The deﬁnitions of the mappings and the theorem that establishes the relationship between the preferred argumentation semantics and the logic programming semantics M M r are described next.
Voronkov proofs or split proofs) some predicate and/or function symbols are declared to have colors, while other symbols are uncolored. A symbol, term, literal or formula using a color are called colored, otherwise they are called transparent. A derivation is called wellcolored if any inference can use symbols of at most one color. Any inference having at least one colored premise and a transparent conclusion is called a symbol eliminating inference. Following the symbol elimination approach of , loop invariant generation can be thus be addressed using colors, as follows.
Within a 1 second time limit a large set of complex and useful quantified invariants have been generated for each example we tried. Case Studies on Invariant Generation Using a Saturation Theorem Prover 13 Table 3. Invariant generation by symbol elimination with Vampire, within 1 second time limit Loop Initialisation  a = 0; while (a < m) do A[a] = 0; a = a + 1 end do Copy  a = 0; while (a < m) do B[a] = A[a]; a = a + 1 end do Vararg  a = 0; while (A[a] > 0) do a=a+1 end do Partition  a = 0; b = 0; c = 0; while (a < m) do if (A[a] >= 0) then B[b] = A[a]; b = b + 1 else C[c] = A[a]; c = c + 1 end if; a=a+1 end do Partition Init  a = 0; c = 0; while (a < m) do if (A[a] == B[a]) then C[c] = a; c = c + 1 end if; a=a+1 end do Shift a = 0; while (a < m) do A[a + 1] = A[a]; a = a + 1 end do SEI Min SEI Inv of interest Generated invariants implying Inv 15 5 ∀x : 0 ≤ x < a ⇒ A[x] = 0 inv7: ∀x0 , x1 , x2 : 0 = x0 ∨ x1 = x2 ∨ A(x1 ) = x0 ∨ ¬a > x2 ∨ ¬x2 ≥ 0 24 5 ∀x : 0 ≤ x < a ⇒ B[x] = A[x] inv8: ∀x0 , x1 : A[x0 ] = B[x1 ] ∨ x0 = x1 ∨ ¬a > x0 ∨ ¬x0 ≥ 0 1 1 ∀x : 0 ≤ x < a ⇒ A[x] > 0 inv0: ∀x0 : ¬a > x0 ∨ ¬x0 ≥ 0∨ A(x0 ) > 0 38 ∀x : 0 ≤ x < b ⇒ B[x] ≥ 0∧ ∃y : B[x] = A[y] 166 inv1: ∀x0 : inv81: ∀x0 : A(sk 2 (x0 )) ≥ 0∨ ¬b > x0 ∨ ¬x0 ≥ 0 ¬b > x0 ∨ ¬x0 ≥ 0∨ A(sk 2 (x0 )) = B(x0 ) inv0: ∀x0 : A(sk 1 (x0 )) = B(sk 1 (x0 ))∨ ¬c > x0 ∨ ¬x0 ≥ 0 168 24 24 5 ∀x : 0 ≤ x < c ⇒ A[C[x]] = B[C[x]] inv30: ∀x0 , x1 , x2 : sk 1 (x0 ) = x1 ∨ x0 = x2 ∨ ¬c > x0 ∨ ¬x0 ≥ 0 ∨ C(x2 ) = x1 inv5: ∀x0 , x1 , x2 : x0 + 1 = x1 ∨ A[x0 ] = x2 ∨ A[x1 ] = x2 ∨ ∀x : 0 ≤ x ≤ a ⇒ ¬a > x0 ∨ ¬x0 ≥ 0 A[x] = A inv13: ∀x0 , x1 : A = x0 ∨ x1 = 1 ∨ A[x1 ] = x0 ∨ 3.