the proceedings contain 10 papers. the topics discussed include: minimum free energy, partition function and kinetics simulation algorithms for a multistranded scaffolded DNA computer;DNA tile self-assembly for 3d-sur...
ISBN:
(纸本)9783959772976
the proceedings contain 10 papers. the topics discussed include: minimum free energy, partition function and kinetics simulation algorithms for a multistranded scaffolded DNA computer;DNA tile self-assembly for 3d-surfaces: towards genus identification;on the runtime of chemical reaction networks beyond idealized conditions;rational design of DNA sequences with non-orthogonal binding interactions;revisiting hybridization kinetics with improved elementary step simulation;reversible bond logic;accelerating self-assembly of crisscross slat systems;thermodynamically driven signal amplification;optimal information encoding in chemical reaction networks;and complexity of reconfiguration in surface chemical reaction networks.
Inversion is an important and useful program transformation and has been studied in various programming language paradigms. Semi-inversion is more general than just swapping the input and output of a program;instead, ...
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ISBN:
(纸本)9783030452599;9783030452605
Inversion is an important and useful program transformation and has been studied in various programming language paradigms. Semi-inversion is more general than just swapping the input and output of a program;instead, parts of the input and output can be freely swapped. In this paper, we present a polyvariant semi-inversion algorithm for conditional constructor term rewriting systems. these systems can model logic and functional languages, which have the advantage that semi-inversion, as well as partial and full inversion, can be studied across different programming paradigms. the semi-inverter makes use of local inversion and a simple but effective heuristic and is proven to be correct. A Prolog implementation is applied to several problems, including inversion of a simple encrypter and of a program inverter for a reversible language.
CP-logic is a probabilistic extension of the logic FO(ID). Unlike ASP, both of these logics adhere to a Tarskian informal semantics, in which interpretations represent objective states-of-affairs. In other words, thes...
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the proceedings contain 19 papers. the topics discussed include: the Orc programming language;keep it small, keep it real: efficient run-time verification of web service compositions;approximated context-sensitive ana...
ISBN:
(纸本)3642021379
the proceedings contain 19 papers. the topics discussed include: the Orc programming language;keep it small, keep it real: efficient run-time verification of web service compositions;approximated context-sensitive analysis for parameterized verification;verification of parameterized systems with combinations of abstract domains;on model-checking optimistic replication algorithms;a software platform for timed mobility and timed interaction;modeling, validation, and verification of PCEP using the IF language;distinguing non-deterministic timed finite state machines;system model-based definition of modeling language semantics;typing component-based communication systems;epistemic logic for the applied Pi calculus;on process-algebraic proof methods for fault tolerant distributed systems;using first-order logic to reason about submodule construction;a model-checking approach for service component architectures;and dynamic symbolic execution of distributed concurrent objects.
We consider disjunctive logic programs without function symbols but with existential quantification in rule heads, under the semantics of general stable models. there are at least two interesting prospects in these pr...
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We consider disjunctive logic programs without function symbols but with existential quantification in rule heads, under the semantics of general stable models. there are at least two interesting prospects in these programs. the first is that a program can be made more succinct by using existential variables, and the second is on the potential in representing defeasible ontological knowledge by these logic programs. this paper studies some of the properties of these programs. First, we show a simple yet intuitive definition of stable models for these programs that does not resort to second-order logic. Second, the stable models of these programs can be characterized by an extension of progression for disjunctive programs, which provides a native characterization of justification for stable models. We then study the decidability issue. While the stable model existence problem for safe disjunctive programs is decidable, with existential quantification allowed in rule heads the problem becomes undecidable. We identify an interesting decidable fragment by exploring a new notion of stratification over existential quantification.
Domain-specific heuristics are a crucial technique for the efficient solving of problems that are large or computationally hard. Answer Set programming (ASP) systems support declarative specifications of domain-specif...
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We study the problem of finding optimal plans for multiple teams of robots through a mediator, where each team is given a task to complete in its workspace on its own and where teams are allowed to transfer robots bet...
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We study the problem of finding optimal plans for multiple teams of robots through a mediator, where each team is given a task to complete in its workspace on its own and where teams are allowed to transfer robots between each other, subject to the following constraints: 1) teams (and the mediator) do not know about each other's workspace or tasks (e.g., for privacy purposes);2) every team can lend or borrow robots, but not both (e.g., transportation/calibration of robots between/for different workspaces is usually costly). We present a mathematical definition of this problem and analyze its computational complexity. We introduce a novel, logic-based method to solve this problem, utilizing action languages and answer set programming for representation, and the state-of-the-art ASP solvers for reasoning. We show the applicability and usefulness of our approach by experiments on various scenarios of responsive and energy-efficient cognitive factories.
In parallel logicprogramming systems that exploit both and-parallelism and or-parallelism, a problem arises that is how to distribute processors between the dynamically varying amounts of and-work and or-work that ar...
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Answer Set programming (ASP) is a powerful form of declarative programming used in areas such as planning or reasoning. ASP solvers enforce stable model semantics, which rule out solutions representing certain kinds o...
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Answer Set programming (ASP) is a powerful form of declarative programming used in areas such as planning or reasoning. ASP solvers enforce stable model semantics, which rule out solutions representing certain kinds of circular reasoning. Unfortunately, current ASP solvers are incapable of solving problems involving cyclic dependencies between multiple integer or continuous quantities effectively. In this paper, we generalize the notion of stable models to bound founded variables with arbitrary domains, where bounds on such variables need to be justified by some rule in the program in order for the model to be stable. We show how to handle significantly more general rule forms where bound founded variables can act as head or body variables, and where head and body variables can be related via complex constraints subject to certain monotonicity requirements. We describe a new unfounded set detection algorithm which allows us to enforce this generalization of the stable model semantics. We also show how these unfounded sets can be explained in order to allow effective conflict-directed clause learning. the new solver merges the best features of CP, SAT and ASP solvers and allows new types of problems to be solved very efficiently.
In real-world supervised Machine Learning tasks, the learned theory can be deemed as valid only until there is evidence to the contrary (i.e., new observations that are wrongly classified by the theory). In such a cas...
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In real-world supervised Machine Learning tasks, the learned theory can be deemed as valid only until there is evidence to the contrary (i.e., new observations that are wrongly classified by the theory). In such a case, incremental approaches allow to revise the existing theory to account for the new evidence, instead of learning a new theory from scratch. In many cases, positive and negative examples are provided in a mixed and unpredictable order, which requires generalization and specialization refinement opearators to be available for revising the hypotheses in the existing theory when it is inconsistent withthe new examples. the space of Datalog Horn clauses under the OI assumption allows the existence of refinement operators that fulfill desirable properties. However, the versions of these operators currently available in the literature are not able to handle some refinement tasks. the objective of this work is paving the way for an improved version of the specialization operator, aimed at extending its applicability.
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