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检索条件"任意字段=36th International Conference on Logic Programming, ICLP 2020"

共 105 条记录，以下是71-80 订阅

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Fast Context Adaptation via Meta-Learning 36

Fast Context Adaptation via Meta-Learning

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36th international conference on Machine Learning (ICML)

作者： Zintgraf, Luisa Shiarlis, Kyriacos Kurin, Vitaly Hofmann, Katja Whiteson, Shimon Univ Oxford Oxford England Latent Logic Oxford England Microsoft Res Redmond WA USA

ISBN: (纸本)9781510886988

We propose CAVIA for meta-learning, a simple extension to MAML that is less prone to meta-overfitting, easier to parallelise, and more interpretable. CAVIA partitions the model parameters into two parts: context parameters that serve as additional input to the model and are adapted on individual tasks, and shared parameters that are meta-trained and shared across tasks. At test time, only the context parameters are updated, leading to a low-dimensional task representation. We show empirically that CAVIA outperforms MAML for regression, classification, and reinforcement learning. Our experiments also high-light weaknesses in current benchmarks, in that the amount of adaptation needed in some cases is small.

关键词： Reinforcement learning

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An interpretable logic KBQA method based on open-source large language models 36

An interpretable logic KBQA method based on open-source larg...

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36th international conference on Software Engineering and Knowledge Engineering, SEKE 2024

作者： Xu, Bicheng Peng, Rong Ding, Yongchang Fang, Lin School of Computer Science Wuhan University Hubei Wuhan China

ISBN: (纸本)1891706594

Knowledge Base Question Answering (KBQA) aims to find correct answers to natural language questions by reasoning over large-scale knowledge bases. the main challenge is multi-hop reasoning, which requires inferring answers through multiple edges and nodes. Due to high data annotation costs, most datasets only provide final answer annotations, leaving the reasoning process unknown. the model cannot provide the reasoning path along with the answer, making the answer uninterpretable. To address this, we propose a generation-retrieval multi-hop KBQA method combining large language models (LLMs) and the logic programming language Prolog. In the generation phase, we fine-tune the open-source LLMs to generate the logical form of the corresponding prolog representation for the natural language question. In the retrieval phase, the model uses prolog query to reasoning over the KB to get the final answer and the reasoning path. A transparent reasoning path also helps identify and correct errors, enhancing the model’s reliability and practicality. Experimental results on two standard KBQA datasets, MetaQA and WebQSP, demonstrate that our method outperforms existing models in both performance and interpretability. © 2024 Knowledge Systems Institute Graduate School. All rights reserved.

关键词： PROLOG (programming language)

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Overview of the 2017 CAD contest at ICCAD: Invited paper 36

Overview of the 2017 CAD contest at ICCAD: Invited paper

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36th IEEE/ACM international conference on Computer-Aided Design, ICCAD 2017

作者： Kim, Myung-Chul Huang, Shih-Hsu Lin, Rung-Bin Nakatake, Shigetoshi IBM Corporation AustinTX78758 United States Department of Electronic Engineering Chung Yuan Christian University Taoyuan32023 Taiwan Department of Computer Science and Engineering Yuan Ze University Taoyuan32023 Taiwan Department of Information and Media Engineering University of Kitakyushu Fukuoka808-0135 Japan

ISBN: (纸本)9781538630938

the CAD Contest at ICCAD[1], [2], [3], [4], [5], [6] is a challenging, multi-month R&D competition, focusing on modern and practical problems at the forefront of Electronic Design Automation (EDA). In its sixth year, the 2017 CAD Contest at ICCAD is among the premier worldwide academic programming contests, attracting 122 teams from 10 different regions/countries. this year, three contest problems in the areas of ECO logic synthesis, ECO routing and placement legalization for the advanced nodes are called for competition. We hope that the contest evaluation frameworks and benchmarks boost research on these critical problems and help EDA community discover novel, efficient, high-quality solutions to advance the state-of-the-art in EDA. © 2017 IEEE.

关键词： logic Synthesis

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Approximate Relational Reasoning for Quantum Programs 36th

Approximate Relational Reasoning for Quantum Programs

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36th international conference on Computer-Aided Verification (CAV)

作者： Yan, Peng Jiang, Hanru Yu, Nengkun Univ Technol Sydney Sydney NSW Australia Beijing Inst Math Sci & Applicat Beijing Peoples R China SUNY Stony Brook Stony Brook NY 11794 USA

ISBN: (纸本)9783031656323;9783031656330

Quantum computation is inevitably subject to imperfections in its implementation. these imperfections arise from various sources, including environmental noise at the hardware level and the introduction of approximate implementations by quantum algorithm designers, such as lower-depth computations. Given the significant advantage of relational logic in program reasoning and the importance of assessing the robustness of quantum programs between their ideal specifications and imperfect implementations, we design a proof system to verify the approximate relational properties of quantum programs. We demonstrate the effectiveness of our approach by providing the first formal verification of the renowned low-depth approximation of the quantum Fourier transform. Furthermore, we validate the approximate correctness of the repeat-until-success algorithm. From the technical point of view, we develop approximate quantum coupling as a fundamental tool to study approximate relational reasoning for quantum programs, a novel generalization of the widely used approximate probabilistic coupling in probabilistic programs, answering a previously posed open question for projective predicates.

关键词： Relational Hoare logic Approximating Reasoning Quantum programming Languages

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Explanation Graphs for Stable Models of Labelled logic Programs 39

Explanation Graphs for Stable Models of Labelled Logic Progr...

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39th international conference on logic programming Workshops, iclp Workshops 2023

作者： Cabalar, Pedro Muñiz, Brais University of Coruña Spain

In this paper, we introduce the notion of an explanation graph for any model of a logic program. For each true atom in the model, the graph contains a proof that uses program rules represented by rule labels. A model may have zero, one or several explanation graphs: when it has at least one, it is called a justified model. We prove that all stable models are justified whereas, in general, the opposite does not hold, at least for disjunctive programs. With the purpose of just keeping the information that is considered to be salient, we discuss several operations on explanation graphs. these include the removal of incoming or outgoing edges of a node, but also what we define as node forgetting, that is, removing a node while keeping the connectivity of the rest of the graph. then, we explain how these theoretical concepts constitute the foundation of xclingo 2.0, a tool for explainable Answer Set programming (ASP) that uses, in its turn, an ASP encoding to generate explanations. the tool translates the original program into a meta-program that constitutes the core of xclingo 2.0. We explain this encoding and prove its soundness and completeness with respect to explanation graphs. through a practical example, we illustrate the general use of the tool and its input language based on annotations. Finally, we show how critical these annotations can be for designing meaningful, summarised, natural language explanations. 2022 Copyright for this paper by its authors.

关键词： Encoding (symbols)

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GALOIS: Boosting Deep Reinforcement Learning via Generalizable logic Synthesis 36

GALOIS: Boosting Deep Reinforcement Learning via Generalizab...

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36th conference on Neural Information Processing Systems (NeurIPS)

作者： Cao, Yushi Li, Zhiming Yang, Tianpei Zhang, Hao Zheng, Yan Li, Yi Hao, Jianye Liu, Yang Tianjin Univ Coll Intelligence & Comp Tianjin Peoples R China Nanyang Technol Univ Singapore Singapore Univ Alberta Edmonton AB Canada

ISBN: (纸本)9781713871088

Despite achieving superior performance in human-level control problems, unlike humans, deep reinforcement learning (DRL) lacks high-order intelligence (e.g., logic deduction and reuse), thus it behaves ineffectively than humans regarding learning and generalization in complex problems. Previous works attempt to directly synthesize a white-box logic program as the DRL policy, manifesting logic-driven behaviors. However, most synthesis methods are built on imperative or declarative programming, and each has a distinct limitation, respectively. the former ignores the cause-effect logic during synthesis, resulting in low generalizability across tasks. the latter is strictly proof-based, thus failing to synthesize programs with complex hierarchical logic. In this paper, we combine the above two paradigms together and propose a novel Generalizable logic Synthesis (GALOIS) framework to synthesize hierarchical and strict cause-effect logic programs. GALOIS leverages the program sketch and defines a new sketch-based hybrid program language for guiding the synthesis. Based on that, GALOIS proposes a sketch-based program synthesis method to automatically generate white-box programs with generalizable and interpretable cause-effect logic. Extensive evaluations on various decision-making tasks with complex logic demonstrate the superiority of GALOIS over mainstream baselines regarding the asymptotic performance, generalizability, and great knowledge reusability across different environments.

关键词： Reinforcement learning

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SMT-Based Symbolic Model-Checking for Operator Precedence Languages 36th

SMT-Based Symbolic Model-Checking for Operator Precedence La...

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36th international conference on Computer-Aided Verification (CAV)

作者： Chiari, Michele Geatti, Luca Gigante, Nicola Pradella, Matteo TU Wien Treitlstr 3 A-1040 Vienna Austria Univ Udine Udine Italy Free Univ Bozen Bolzano Bolzano Italy Politecn Milan Milan Italy

ISBN: (纸本)9783031656262;9783031656279

Operator Precedence Languages (OPL) have been recently identified as a suitable formalism for model checking recursive procedural programs, thanks to their ability of modeling the program stack. OPL requirements can be expressed in the Precedence Oriented Temporal logic (POTL), which features modalities to reason on the natural matching between function calls and returns, exceptions, and other advanced programming constructs that previous approaches, such as Visibly Pushdown Languages, cannot model effectively. Existing approaches for model checking of POTL have been designed following the explicit-state, automata-based approach, a feature that severely limits their scalability. In this paper, we give the first symbolic, SMT-based approach for model checking POTL properties. While previous approaches construct the automaton for both the POTL formula and the model of the program, we encode them into a (sequence of) SMT formulas. the search of a trace of the model witnessing a violation of the formula is then carried out by an SMT-solver, in a Bounded Model Checking fashion. We carried out an experimental evaluation, which shows the effectiveness of the proposed solution.

关键词： SMT-based Model Checking Tree-shaped Tableau Temporal logic Operator Precedence Languages

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A Dataset of Contractual Events in Court Decisions 39

A Dataset of Contractual Events in Court Decisions

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39th international conference on logic programming Workshops, iclp Workshops 2023

作者： Paulino-Passos, Guilherme Satoh, Ken Toni, Francesca Department of Computing Imperial College London United Kingdom Principles of Informatics Research Division National Institute of Informatics Tokyo Japan

the promise of automation of legal reasoning is developing technology that reduces human time required for legal tasks or that improves human performance on such tasks. In order to do so, different methods and systems based on logic programming were developed. However, in order to apply such methods on legal data, it is necessary to provide an interface between human users and the legal reasoning system, and the most natural interface in the legal domain is natural language, in particular, written text. In order to perform reasoning in written text using logic programming methods, it is then necessary to map expressions in text to atoms and predicates in the formal language, a task referred generally as information extraction. In this work, we propose a new dataset for the task of information extraction, in particular event extraction, in court decisions, focusing on contracts. Our dataset captures contractual relations and events that affect them in some way, such as negotiations preceding a (possible) contract, the execution of a contract, or its termination. We conducted text annotation with law students and graduates, resulting in a dataset with 207 documents, 3934 sentences, 4440 entities, and 1794 events. We describe here this resource, the annotation process, its evaluation with inter-annotator agreement metrics, and discuss challenges during the development of this resource and for the future. 2023 Copyright for this paper by its authors.

关键词： logic programming

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Design of Accurate Stochastic Number Generators with Noisy Emerging Devices for Stochastic Computing 17

Design of Accurate Stochastic Number Generators with Noisy E...

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IEEE/ACM 36th international conference on Computer-Aided Design (ICCAD)

作者： Yang, Meng Hayes, John P. Fan, Deliang Qian, Weikang Shanghai Jiao Tong Univ Univ Michigan Shanghai Jiao Tong Univ Joint Inst Shanghai Peoples R China Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA Univ Cent Florida Dept Elect Engn & Comp Sci Orlando FL 32816 USA

ISBN: (纸本)9781538630938

Stochastic computing (SC) is an unconventional computing paradigm that operates on stochastic bit streams. It has gained attention recently because of the very low area and power needs of its computing core. SC relies on stochastic number generators (SNGs) to map input binary numbers to stochastic bit streams. A conventional SNG comprises a random number source (RNS), typically an LFSR, and a comparator. It needs far more area and power than the SC core, offsetting the latter's main advantages. To mitigate this problem, SNGs employing emerging nanoscale devices such as memristors and spintronic devices have been proposed. However, these devices tend to have large errors in their output probabilities due to unpredictable variations in their fabrication processes and noise in their control signals. We present a novel method of exploiting such devices to design a highly accurate SNG. It is built around an RNS that generates uniformly distributed random numbers under ideal (nominal) conditions. It also has a novel error-cancelling probability conversion circuit (ECPCC) that guarantees very high accuracy in the output probability under realistic conditions when the RNS is subject to errors. An ECPCC can also be used to generate maximally correlated stochastic streams, a useful property for some applications.

关键词： Generators Memristors logic gates Switches Stochastic processes Noise measurement programming

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Expanding design pattern to support parallel programming

Expanding design pattern to support parallel programming

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Technology of Object-Oriented Languages and Systems (TOOLS)

作者： J.Y. Wan Y.Q. Sun J.Y. Xue Shanghai Jiaotong University China Jiangxi Normal University China

the design pattern concept is widely used in large object-oriented software development, but this should not be limited to the object-oriented field: it can be used in many other areas. Explicit parallel programming is well-known to be complex and error-prone, and design patterns can ease this work. this paper introduces a pattern-based approach for parallel programming, in which we classify design patterns into two levels to support (a) the parallel algorithm design phase and (b) the parallel coding phase, respectively. through this approach, a programmer doesn't need much additional knowledge about parallel computing; what he need to do is to describe the problem he wants to solve and offer some parameters, sequential code or components. We demonstrate this approach with a case study in this paper.

关键词： Parallel programming programming profession Parallel processing Concurrent computing Algorithm design and analysis Problem-solving Parallel algorithms Functional programming logic programming Object oriented programming

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