Logics, automata and algorithms for
graphs
p. madhusudan(madhu)
University of Illinois at Urbana-Champaign, USA
What is logic? Logic is a precise mathematical language where every sentence has a precise meaning.
Example: FOL (N, +, <, 0, 1) 8x 9y (x · y) -- every number has some
number greater than it
Example: Regular expressions
Non-example: English; law books
Logics on graphs
A graph G=(V,E) can be treated as a logical structure.
The set of vertices V is the universe; E is a relation
Eg. Every vertex is adjacent to some vertex: 8x 9y E(x,y)
Logics on graphs can hence state algorithmic problems on graphs
Logics on graphs Two main problems:
Membership: Given a graph G, solve the algorithmic problem for G. i.e. does G satisfy ? Eg. Is the graph 3-colorable?
Emptiness: Given is there some graph that satisfies it?Eg. planar and 5-colorable but not 4-colorable -- 4 color theorem
What are automata? Automata are machines that process structures
(graphs), and accept or reject them.
Eg. Automata on words, automata on trees
Automata usually have a decidable membership/emptiness problems
(unlike Turing machines).
Hence give decidable algorithms for structures Logic Automata Eg. FOL (N, +, 0, <) is decidable using automata theory
Algorithms
Algorithms on structures.
Algorithmic problem Logic eg. 3 colorability of graphs can be expressed using logic
Leads to designing linear time algorithms for problems on particular classes of graphs
ThemeAlgorithmic problem Logic Automata Algorithm
Overview Overview (Lec 1) Automata on words: (Lec 2)
Closure properties, monadic second order logic (MSO), equivalence of MSO and regular languages
Decidability of Presburger arithmetic using automata (Lec 3) Automata on trees: (Lec 4) Closure properties, top-down vs bottom-up tree automata,
MSO, equivalence of MSO and regular tree languages.
Deciding MSO on Series parallel graphs using tree interpretations (Lec 5)
Deciding MSO on Nested words using tree interpretations Applications to XML stream processing (Lec 6)
Overview Graphs of bounded tree width (Lec 7); Courcelle’s thm: MSO on BTW graphs is solvable in linear time (Lec 8)
Decidability of satisfiability for logics on graphs; and Finite model theory (Lec 9 and Lec 10)
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