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60
Multilevel logic synthesis
 Proc. IEEE
"... A survey of logic synthesis techniques for multilevel combinational logic is presented. The goal is to provide more indepth background and perspective for people interested in pursuing or assessing some of the topics in this emerging field. Introductions, capsule summaries, and, in some cases, deta ..."
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Cited by 120 (20 self)
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A survey of logic synthesis techniques for multilevel combinational logic is presented. The goal is to provide more indepth background and perspective for people interested in pursuing or assessing some of the topics in this emerging field. Introductions, capsule summaries, and, in some cases, detailed analysis, of the synthesis methods which have become established as practically significant are provided. Also included are some methods which
Planning with Pattern Databases
 PROCEEDINGS OF THE 6TH EUROPEAN CONFERENCE ON PLANNING (ECP01)
, 2001
"... Heuristic search planning eectively #12;nds solutions for large planning problems, but since the estimates are either not admissible or too weak, optimal solutions are found in rare cases only. In contrast, heuristic pattern databases are known to signi#12;cantly improve lowerbound estimates for opt ..."
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Cited by 116 (16 self)
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Heuristic search planning eectively #12;nds solutions for large planning problems, but since the estimates are either not admissible or too weak, optimal solutions are found in rare cases only. In contrast, heuristic pattern databases are known to signi#12;cantly improve lowerbound estimates for optimally solving challenging singleagent problems like the 24Puzzle or Rubik's Cube.
This paper studies the eect of pattern databases in the context of deterministic planning. Given afixed state description based on instantiated predicates, we provide a general abstraction scheme to automatically create admissible domainindependent memorybased heuristics for planning problems, where abstractions are found in factorizing the planning space. We evaluate the impact of pattern database heuristics in A* and hill climbing algorithms for a collection of benchmark domains.
Exhibiting Knowledge in Planning Problems to Minimize State Encoding Length
 In ECP
, 1999
"... In this paper we present a generalpurposed algorithm for transforming a planning problem specified in Strips into a concise state description for single state or symbolic exploration. The process of finding a state description consists of four phases. In the first phase we symbolically analyze the ..."
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Cited by 50 (15 self)
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In this paper we present a generalpurposed algorithm for transforming a planning problem specified in Strips into a concise state description for single state or symbolic exploration. The process of finding a state description consists of four phases. In the first phase we symbolically analyze the domain specification to determine constant and oneway predicates, i.e. predicates that remain unchanged by all operators or toggle in only one direction, respectively. In the second phase we symbolically merge predicates which lead to a drastic reduction of state encoding size, while in the third phase we constrain the domains of the predicates to be considered by enumerating the operators of the planning problem. The fourth phase combines the result of the previous phases.
Heuristic Search
, 2011
"... Heuristic search is used to efficiently solve the singlenode shortest path problem in weighted graphs. In practice, however, one is not only interested in finding a short path, but an optimal path, according to a certain cost notion. We propose an algebraic formalism that captures many cost notions ..."
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Cited by 40 (22 self)
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Heuristic search is used to efficiently solve the singlenode shortest path problem in weighted graphs. In practice, however, one is not only interested in finding a short path, but an optimal path, according to a certain cost notion. We propose an algebraic formalism that captures many cost notions, like typical Quality of Service attributes. We thus generalize A*, the popular heuristic search algorithm, for solving optimalpath problem. The paper provides an answer to a fundamental question for AI search, namely to which general notion of cost, heuristic search algorithms can be applied. We proof correctness of the algorithms and provide experimental results that validate the feasibility of the approach.
Timeconstrained Code Compaction for DSPs
 IEEE Trans. on VLSI Systems
, 1995
"... DSP algorithms in most cases are subject to hard realtime constraints. In case of programmable DSP processors, meeting those constraints must be ensured by appropriate code generation techniques. For processors offering instructionlevel parallelism, the task of code generation includes code compac ..."
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Cited by 38 (14 self)
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DSP algorithms in most cases are subject to hard realtime constraints. In case of programmable DSP processors, meeting those constraints must be ensured by appropriate code generation techniques. For processors offering instructionlevel parallelism, the task of code generation includes code compaction. The exact timing behavior of a DSP program is only known after compaction. Therefore, realtime constraints should be taken into account during the compaction phase. While most known DSP code generators rely on rigid heuristics for that phase, this paper proposes a novel approach to local code compaction based on an Integer Programming model, which obeys exact timing constraints. Due to a general problem formulation, the model also obeys encoding restrictions and possible side effects. 1 1 Introduction & related work Design requirements for embedded systems including DSP functionality strongly differ from those for interactive environments such as workstations. While in the latter ca...
Computing Strongly Connected Components in a Linear Number of Symbolic Steps
, 2002
"... We present an algorithm that computes in a linear number of symbolic steps (O(jV j)) the strongly connected components (sccs) of a graph G = hV; Ei represented by an Ordered Binary Decision Diagram (OBDD). This result matches the complexity of the (celebrated) Tarjan 's algorithm operating on e ..."
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Cited by 24 (2 self)
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We present an algorithm that computes in a linear number of symbolic steps (O(jV j)) the strongly connected components (sccs) of a graph G = hV; Ei represented by an Ordered Binary Decision Diagram (OBDD). This result matches the complexity of the (celebrated) Tarjan 's algorithm operating on explicit data structures. To date, the best algorithm for the above problem works in (jV j log jV j) symbolic steps ([BGS00]).
From Bisimulation to Simulation  Coarsest Partition Problems
 J. Automated Reasoning
, 2002
"... The notions of bisimulation and simulation are used for graph reduction and are widely employed in many areas: Modal Logic, Concurrency Theory, Set Theory, Formal Verification, etc. In particular, in the context of Formal Verification they are used to tackle the socalled stateexplosion problem. ..."
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Cited by 19 (1 self)
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The notions of bisimulation and simulation are used for graph reduction and are widely employed in many areas: Modal Logic, Concurrency Theory, Set Theory, Formal Verification, etc. In particular, in the context of Formal Verification they are used to tackle the socalled stateexplosion problem.
Protocol verification with heuristic search
, 2001
"... We present an approach to reconcile explicit state model checking and heuristic directed search. We provide experimental evidence that the model checking problem for concurrent systems, such as communications protocols, can be solved more efficiently, since finding a state violating a property ..."
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Cited by 19 (5 self)
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We present an approach to reconcile explicit state model checking and heuristic directed search. We provide experimental evidence that the model checking problem for concurrent systems, such as communications protocols, can be solved more efficiently, since finding a state violating a property can be understood as a directed search problem. In our work we combine the expressive power and implementation efficiency of the SPIN model checker with the HSF heuristic search workbench, yielding the HSFSPIN tool that we have implemented. We start off from the A* algorithm and some of its derivatives and define heuristics for various system properties that guide the search so that it finds error states faster. In this paper we focus on safety properties and provide heuristics for invariant and assertion violation and deadlock detection. We provide experimental results for applying HSFSPIN to two toy protocols and one real world protocol, the CORBA GIOP protocol.
Localizing A*
"... Heuristic search in large problem spaces inherently calls for algorithms capable of running under restricted memory. This question has been investigated in a number of articles. However, in general the efficient usage of twolayered storage systems is not further discussed. Even if harddisk ca ..."
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Cited by 15 (8 self)
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Heuristic search in large problem spaces inherently calls for algorithms capable of running under restricted memory. This question has been investigated in a number of articles. However, in general the efficient usage of twolayered storage systems is not further discussed. Even if harddisk capacity is sufficient for the problem instance at hand, the limitation of main memory may still represent the bottleneck for their practical applications. Since breadthfirst and bestfirst strategies do not exhibit any locality of expansion, standard virtual memory management can soon result in thrashing due to excessive page faults. In this paper we propose a new search algorithm and suitable data structures in order to minimize page faults by a local reordering of the sequence of expansions. We prove its correctness and completeness and evaluate it in a realworld scenario of searching a large road map in a commercial route planning system.