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检索条件"丛书名=Lecture notes in artificial intelligence,"

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A Novel Explainable Link Forecasting Framework for Temporal Knowledge Graphs Using Time-Relaxed Cyclic and Acyclic Rules 27th

A Novel Explainable Link Forecasting Framework for Temporal ...

引用

27th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)

作者： Rage, Uday Kiran Maharana, Abinash Polepalli, Krishna Reddy Univ Aizu Aizu Wakamatsu Fukushima Japan Int Inst Informat Technol Hyderabad Telangana India

ISBN: (纸本)9783031333736;9783031333743

Link forecasting in a temporal Knowledge Graph (tKG) involves predicting a future event from a given set of past events. Most previous studies suffered from reduced performance as they disregarded acyclic rules and enforced a tight constraint that all past events must exist in a strict temporal order. This paper proposes a novel explainable rule-based link forecasting framework by introducing two new concepts, namely 'relaxed temporal cyclic and acyclic random walks' and 'link-star rules'. The former concept involves generating rules by performing cyclic and acyclic random walks on a tKG by taking into account the real-world phenomenon that the order of any two events may be ignored if their occurrence time gap is within a threshold value. Link-star rules are a special class of acyclic rules generated based on the natural phenomenon that history repeats itself after a particular time. Link-star rules eliminate the problem of combinatorial rule explosion, thereby making our framework practicable. Experimental results demonstrate that our framework outperforms the state-of-the-art by a substantial margin. The evaluation measures hits@1 and mean reciprocal rank were improved by 45% and 23%, respectively.

关键词： Knowledge Graphs Graph Analytics Forecasting

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On Incremental Pre-processing for SMT 1

引用

29th International Conference on Automated Deduction (CADE)

作者： Bjorner, Nikolaj Fazekas, Katalin Microsoft Res Redmond WA 98052 USA TU Wien Vienna Austria

ISBN: (数字)9783031384998

ISBN: (纸本)9783031384998;9783031384981

We introduce a calculus for incremental pre-processing for SMT and instantiate it in the context of z3. It identifies when powerful formula simplifications can be retained when adding new constraints. Use cases that could not be solved in incremental mode can now be solved incrementally thanks to the availability of pre-processing. Our approach admits a class of transformations that preserve satisfiability, but not equivalence. We establish a taxonomy of pre-processing techniques that distinguishes cases where new constraints are modified or constraints previously added have to be replayed. We then justify the soundness of the proposed incremental pre-processing calculus.

关键词： Equivalence classes

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Off-Policy Reinforcement Learning with Loss Function Weighted by Temporal Difference Error 19th

Off-Policy Reinforcement Learning with Loss Function Weighte...

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19th International Conference on Advanced Intelligent Computing Technology and Applications (ICIC)

作者： Park, Bumgeun Kim, Taeyoung Moon, Woohyeon Nengroo, Sarvar Hussain Har, Dongsoo Korea Adv Inst Sci & Technol Daejeon 34101 South Korea

ISBN: (纸本)9789819947607;9789819947614

Training agents via off-policy deep reinforcement learning algorithm requires a replay memory storing past experiences that are sampled uniformly or non-uniformly to create the batches for training. When calculating the loss function, off-policy algorithms commonly assume that all samples are of equal importance. We introduce a novel algorithm that assigns unequal importance, in the form of a weighting factor, to each experience, based on their distribution of temporal difference (TD) error, for the training objective. Results obtained with uniform sampling from the experiments in eight environments of the OpenAI Gym suite show that the proposed algorithm achieves in one environment 10% increase in convergence speed along with a similar success rate and in the other seven environments 3%-46% increases in success rate or 3%-14% increases in cumulative reward, along with similar convergence speed. The algorithm can be combined with existing prioritization method employing non-uniform sampling. The combined technique achieves 20% increase in convergence speed as compared to the prioritization method alone.

关键词： Experience Off-Policy Reinforcement learning Replay memory Weighting factor TD error

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Targeting the Source: Selective Data Curation for Debiasing NLP Models

Targeting the Source: Selective Data Curation for Debiasing ...

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5th International Workshop on Learning with Imbalanced Domains - Theory and Applications / European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)

作者： Gaci, Yacine Benatallah, Boualem Casati, Fabio Benabdeslem, Khalid Univ Lyon Lyon France Dublin City Univ Dublin Ireland ServiceNow Palo Alto CA USA

ISBN: (纸本)9783031434143;9783031434150

Unjustified social stereotypes have lately been found to taint the predictions of NLP models. Thus, an increasing amount of research focuses on developing methods to mitigate social bias. Most proposed approaches update the parameters of models post-hoc, running the risk of forgetting the predictive task of interest. In this work, we propose a novel way of debiasing NLP models by debiasing and curating their training data. To do so, we propose an unsupervised pipeline to identify which instances in the training data mention stereotypes that tally with the stereotypes encoded in NLP models. Then we either remove or augment these problematic instances, and train NLP models on less biased data. In this pipeline, we propose three methods to excavate stereotypes encoded in models using likelihoods, attention weights and vector representations. Experiments on the tasks of natural language inference, sentiment analysis and question answering suggest that our methods are better at debiasing downstream models than existing techniques.

关键词： Natural Language Processing Fairness Debiasing Data Curation

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Primum Non Nocere: The Ethical Beginnings of a Non-Axiomatic Reasoning System 1

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16th International Conference on artificial General intelligence (AGI)

作者： Ireland, David CSIRO Australian E Hlth Res Ctr Brisbane Qld Australia

ISBN: (数字)9783031334696

ISBN: (纸本)9783031334689;9783031334696

What is the right action? is a question an agent with artificial general intelligence (AGI) will have to face, especially in applications that deal with the health and well-being of human companions. Previous work has considered psychological aspects for forming ethical decision-making;here we consider a philosophy approach and apply abstract, general principles that drive ethical decision-making. Starting with a maxim that has resonated within the health community: "first, do no harm", we introduce equivalent beliefs and goals to a non-axiomatic reasoning system and examine the sub-goals that are formed. We provide a simple scenario that shows how an AGI system might reason from contrasting, normative ethical theories and how they might combine to provide an ethical framework for AGI to engage in more complex human affairs.

关键词： NARS ethics consequentialism deontological virtue ethics

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An Improved Structure-Based Partial Solution Search for the Examination Timetabling Problem 21st

An Improved Structure-Based Partial Solution Search for the ...

引用

21st International Conference on artificial intelligence and Soft Computing (ICAISC)

作者： Rajah, Christopher Pillay, Nelishia Univ KwaZulu Natal Sch Math Stat & Comp Sci Kwa Zulu South Africa Univ Pretoria Dept Comp Sci Gauteng South Africa

ISBN: (纸本)9783031234798;9783031234804

The effectiveness of the Structure-Based Partial Solution Search (SBPSS) in solving the examination timetabling problem (ETP) was shown in previous work. The research presented in this paper extends this work by improving the previous version of the SBPSS. Two improvements were made, namely, additional search operators for exploitation and better control of exploration and exploitation in the deconstruction phase of the approach. The SBPSS was also evaluated on additional benchmark sets, namely the Carter and Yeditepe benchmark sets, in addition to the ITC2007 benchmark set which it was evaluated on in previous work. The improved SBPSS was found to outperform the original version. The performance of the improved SBPSS was also found to be competitive to state-of-the-art approaches applied to the examination timetabling problem, producing two best results for the Carter benchmark set, four best results for the ITC2007 benchmark set, and best results for all instances of the Yeditepe benchmark set.

关键词： Examination timetabling Partial solution space Structure-based search Multipoint search

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Generating Music for Video Games with Real-Time Adaptation to Gameplay Pace 15th

Generating Music for Video Games with Real-Time Adaptation t...

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15th Asian Conference on Intelligent Information and Database Systems (ACIIDS)

作者： Kopel, Marek Antczak, Dawid Walczynski, Maciej Wroclaw Univ Sci & Technol Fac Informat & Commun Technol Wybrzeze Wyspianskiego 27 PL-50370 Wroclaw Poland

ISBN: (纸本)9789819958337;9789819958344

The paper aimed to develop an automatic music generation method for video games that could create various types of music to enhance player immersion and experience, while also being a more cost-effective alternative to human-composed music. The issue of automatic music generation is an interdisciplinary research area that combines topics such as artificial intelligence, music theory, art history, sound engineering, signal processing, and psychology. As a result, the literature to review is vast. Musical compositions can be analyzed from various perspectives, and their applications are extensive, including films, games, and advertisements. Specific methods of music generation may perform better only in a narrow field and range, although we rarely encounter fully computer-generated music nowadays. The proposed algorithm, which utilizes RNN and 4 parameters to control the generation process, was implemented using PyTorch and real-time communication with the game was established using the WebSocket protocol. The algorithm was tested with 14 players who played four levels, each with different background music that was either composed or live-generated. The results showed that the generated music was enjoyed more by the players than the composed music. After implementing improvements from the first round of play tests, all of the generated music received better evaluations than the composed looped music in the second run.

关键词： live music machine learning AI generated content

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Causal Reasoning over Probabilistic Uncertainty 1

引用

16th International Conference on artificial General intelligence (AGI)

作者： Eberding, Leonard M. Thorisson, Kristinn R. Reykjavik Univ Ctr Anal & Design Intelligent Agents Menntavegur 1 Reykjavik Iceland Icelandic Inst Intelligent Machines Reykjavik Iceland

ISBN: (数字)9783031334696

ISBN: (纸本)9783031334689;9783031334696

A system deployed in the real world will need to handle uncertainty in its observations and interventions. For this, we present an approach to introduce uncertainty of state variables in causal reasoning using a constructivist AI architecture. Open questions of how noisy data can be handled and intervention uncertainty can be represented in a causal reasoning system will be addressed. In addition, we will show how handling uncertainty can improve a system's planning and attention mechanisms. We present the reasoning process of the system, including reasoning over uncertainty, in the form of a feed-forward algorithm, highlighting how noisy data and beliefs of states can be included in the process of causal reasoning.

关键词： General Machine intelligence Reasoning Uncertainty

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True Crafted Formula Families for Benchmarking Quantified Satisfiability Solvers 16th

True Crafted Formula Families for Benchmarking Quantified Sa...

引用

16th International Conference on Intelligent Computer Mathematics (CICM)

作者： Heisinger, Simone Seidl, Martina Johannes Kepler Univ Linz Inst Symbol Artificial Intelligence Linz Austria

ISBN: (纸本)9783031427527;9783031427534

As the application of quantified Boolean formulas (QBF) continues to expand in various scientific and industrial domains, the development of efficient QBF solvers and their underlying proving strategies is of growing importance. To understand and to compare different solving approaches, techniques of proof complexity are applied. To this end, formula families have been crafted that exhibit certain properties of proof systems. These formulas are valuable to test and compare specific solver implementations. Traditionally, the focus is on false formulas, in this work we extend the formula generator QBFFam to produce true formulas based on two popular formula families from proof complexity.

关键词： QBF Solver Benchmarking KBKF QParity

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Object Anchoring for Autonomous Robots Using the Spatio-Temporal-Semantic Environment Representation SEEREP 1

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46th German Conference on artificial intelligence (KI)

作者： Niemeyer, Mark Renz, Marian Hertzberg, Joachim German Res Ctr Artificial Intelligence Plan Based Robot Control Grp Osnabruck Germany Osnabruck Univ Knowledge Based Syst Grp Osnabruck Germany

ISBN: (数字)9783031426087

ISBN: (纸本)9783031426070;9783031426087

For single-plant specific weed regulation, robotic systems and agricultural machinery in general have to collect a large amount of temporal and spatial high-resolution sensor data. SEEREP, the Spatio-Temporal-Semantic Environment Representation, can be used to structure and manage such data more efficiently. SEEREP deals with the spatial, temporal and semantic modalities of data simultaneously and provides an efficient query interface for all three modalities that can be combined for high-level analyses. It supports popular robotic sensor data such as images and point clouds, as well as sensor and robot coordinate frames changing over time. This query interface enables high-level reasoning systems as well as other data analysis methods to handle partially unstructured environments that change over time, as for example agricultural environments. But the current methodology of SEEREP cannot store the result of the analysis methods regarding specific objects instances in the world. Especially the results of the anchoring problem which searches for a connection between symbolic and sub-symbolic data cannot be represented nor queried. Thus, we propose a further development of the SEEREP methodology in this paper: For a given object, we link the existing semantic labels in different datasets to a unique common instance, thereby enabling queries for datasets showing this object instance and with this enabling the efficient provision of datasets for object-centric analysis algorithms. Additionally, the results of those algorithms can be stored linked to the instance either by adding facts in a triple-store like manner or by adding further data linked to the instance, like a point, representing the position of the instance. We show the benefits of our anchoring approach in an agricultural setting with the use-case of single-plant specific weed regulation.

关键词： anchoring environment representation selective weeding

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