4,600 research outputs found
Taming Numbers and Durations in the Model Checking Integrated Planning System
The Model Checking Integrated Planning System (MIPS) is a temporal least
commitment heuristic search planner based on a flexible object-oriented
workbench architecture. Its design clearly separates explicit and symbolic
directed exploration algorithms from the set of on-line and off-line computed
estimates and associated data structures. MIPS has shown distinguished
performance in the last two international planning competitions. In the last
event the description language was extended from pure propositional planning to
include numerical state variables, action durations, and plan quality objective
functions. Plans were no longer sequences of actions but time-stamped
schedules. As a participant of the fully automated track of the competition,
MIPS has proven to be a general system; in each track and every benchmark
domain it efficiently computed plans of remarkable quality. This article
introduces and analyzes the most important algorithmic novelties that were
necessary to tackle the new layers of expressiveness in the benchmark problems
and to achieve a high level of performance. The extensions include critical
path analysis of sequentially generated plans to generate corresponding optimal
parallel plans. The linear time algorithm to compute the parallel plan bypasses
known NP hardness results for partial ordering by scheduling plans with respect
to the set of actions and the imposed precedence relations. The efficiency of
this algorithm also allows us to improve the exploration guidance: for each
encountered planning state the corresponding approximate sequential plan is
scheduled. One major strength of MIPS is its static analysis phase that grounds
and simplifies parameterized predicates, functions and operators, that infers
knowledge to minimize the state description length, and that detects domain
object symmetries. The latter aspect is analyzed in detail. MIPS has been
developed to serve as a complete and optimal state space planner, with
admissible estimates, exploration engines and branching cuts. In the
competition version, however, certain performance compromises had to be made,
including floating point arithmetic, weighted heuristic search exploration
according to an inadmissible estimate and parameterized optimization
Fast Adjustable NPN Classification Using Generalized Symmetries
NPN classification of Boolean functions is a powerful technique used in many logic synthesis and technology mapping tools in FPGA design flows. Computing the canonical form of a function is the most common approach of Boolean function classification. In this paper, a novel algorithm for computing NPN canonical form is proposed. By exploiting symmetries under different phase assignments and higher-order symmetries of Boolean functions, the search space of NPN canonical form computation is pruned and the runtime is dramatically reduced. The algorithm can be adjusted to be a slow exact algorithm or a fast heuristic algorithm with lower quality. For exact classification, the proposed algorithm achieves a 30× speedup compared to a state-of-the-art algorithm. For heuristic classification, the proposed algorithm has similar performance as the state-of-the-art algorithm with a possibility to trade runtime for quality
Breaking Instance-Independent Symmetries In Exact Graph Coloring
Code optimization and high level synthesis can be posed as constraint
satisfaction and optimization problems, such as graph coloring used in register
allocation. Graph coloring is also used to model more traditional CSPs relevant
to AI, such as planning, time-tabling and scheduling. Provably optimal
solutions may be desirable for commercial and defense applications.
Additionally, for applications such as register allocation and code
optimization, naturally-occurring instances of graph coloring are often small
and can be solved optimally. A recent wave of improvements in algorithms for
Boolean satisfiability (SAT) and 0-1 Integer Linear Programming (ILP) suggests
generic problem-reduction methods, rather than problem-specific heuristics,
because (1) heuristics may be upset by new constraints, (2) heuristics tend to
ignore structure, and (3) many relevant problems are provably inapproximable.
Problem reductions often lead to highly symmetric SAT instances, and
symmetries are known to slow down SAT solvers. In this work, we compare several
avenues for symmetry breaking, in particular when certain kinds of symmetry are
present in all generated instances. Our focus on reducing CSPs to SAT allows us
to leverage recent dramatic improvement in SAT solvers and automatically
benefit from future progress. We can use a variety of black-box SAT solvers
without modifying their source code because our symmetry-breaking techniques
are static, i.e., we detect symmetries and add symmetry breaking predicates
(SBPs) during pre-processing.
An important result of our work is that among the types of
instance-independent SBPs we studied and their combinations, the simplest and
least complete constructions are the most effective. Our experiments also
clearly indicate that instance-independent symmetries should mostly be
processed together with instance-specific symmetries rather than at the
specification level, contrary to what has been suggested in the literature
On the Structure of Counterexamples to Symmetric Orderings for BDD's
AbstractBinary Decision Diagrams (BDDs) are used to represent boolean functions in a variety of applications. The size of a reduced ordered BDD depends on the ordering of variables. Several researchers have suggested grouping symmetric variables as a promising heuristic for finding good orderings. In this paper we study the conjecture which states that symmetric variables gather in at least one of the optimum variable orders. First, we prove some useful properties of partially symmetric functions. Next, we develop a faster procedure for finding counterexamples to this conjecture that exploits the partitioning of boolean functions into nn-equivalence classes. Third, we study the structure of counterexamples and devise a new and simple method to generate new counterexamples from given counterexamples. Finally, we present different kinds of counterexamples, which show that boolean functions are very diverse with respect to where symmetric orders can fall in the range from optimal orders to worst-case orders
From Objective Amplitudes to Bayesian Probabilities
We review the Consistent Amplitude approach to Quantum Theory and argue that
quantum probabilities are explicitly Bayesian. In this approach amplitudes are
tools for inference. They codify objective information about how complicated
experimental setups are put together from simpler ones. Thus, probabilities may
be partially subjective but the amplitudes are not.Comment: 10 pages, 2 figures. Invited paper presented at the International
Conference on Foundations of Probability and Physics - 4 (Vaxjo University,
Sweden, 2006). The various versions reflect my attempts to include the
figures in the main body of the pape
Symmetry Properties of Nested Canalyzing Functions
Many researchers have studied symmetry properties of various Boolean
functions. A class of Boolean functions, called nested canalyzing functions
(NCFs), has been used to model certain biological phenomena. We identify some
interesting relationships between NCFs, symmetric Boolean functions and a
generalization of symmetric Boolean functions, which we call -symmetric
functions (where is the symmetry level). Using a normalized representation
for NCFs, we develop a characterization of when two variables of an NCF are
symmetric. Using this characterization, we show that the symmetry level of an
NCF can be easily computed given a standard representation of . We also
present an algorithm for testing whether a given -symmetric function is an
NCF. Further, we show that for any NCF with variables, the notion of
strong asymmetry considered in the literature is equivalent to the property
that is -symmetric. We use this result to derive a closed form
expression for the number of -variable Boolean functions that are NCFs and
strongly asymmetric. We also identify all the Boolean functions that are NCFs
and symmetric.Comment: 17 page
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